Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Changes in the flood frequency in the Mahanadi basin under observed and projected future climate

NASA Astrophysics Data System (ADS)

Modi, P. A.; Lakshmi, V.; Mishra, V.

2017-12-01

The Mahanadi river basin is vulnerable to multiple types of extreme events due to its topography and river networks. These extreme events are not efficiently captured by the current LSMs partly due to lack of spatial hydrological data and uncertainty in the models. This study compares and evaluates the hydrologic simulations of the recently developed community Noah model with multi-parameterization options which is an upgradation of baseline Noah LSM. The model is calibrated and validated for the Mahanadi river basin and is driven by major atmospheric forcing from the Indian Meteorological Department (IMD), Global Precipitation Measurement (GPM), Tropical rainfall Measurement Mission (TRMM) and Multi-Source Weighted-Ensemble Precipitation (MSWEP designed for hydrological modeling) precipitation datasets along with some additional forcing derived from the VIC model at 0.25-degree spatial resolution. The Noah-MP LSM is calibrated using observed daily streamflow data from 1978-1989 (India-WRIS) at the gauge stations with least human interventions with a Nash Sutcliffe Efficiency higher than 0.60. Noah MP was calibrated using different schemes for runoff with variation in all parameters sensitive to surface and sub-surface runoff. Streamflow routing was performed using a stand-alone model (VIC model) to route daily model runoff at required gauge station. Surface runoff is mainly affected by the uncertainties in major atmospheric forcing and highly sensitive parameters pertaining to soil properties. Noah MP is validated using observed streamflow from 1975-2010 which indicates the consistency of streamflow with the historical observations (NSE>0.65) thus indicating an increase in probability of future flood events.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Assessing and mitigating uncertainties in the Noah-MP land-model simulations over the Tibet Plateau region

NASA Astrophysics Data System (ADS)

Zhang, G.; Chen, F.; Gan, Y.

2017-12-01

Assessing and mitigating uncertainties in the Noah-MP land-model simulations over the Tibet Plateau region Guo Zhang1, Fei Chen1,2, Yanjun Gan11State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China 2National Center for Atmospheric Research, Boulder, Colorado, USA Uncertainties in the Noah with multiparameterization (Noah-MP) land surface model were assessed through physics ensemble simulations for four sparsely-vegetated sites located in the Tibetan Plateau region. Those simulations were evaluated using observations at the four sites during the third Tibetan Plateau Experiment (TIPEX III).The impacts of uncertainties in precipitation data used as forcing conditions, parameterizations of sub-processes such as soil organic matter and rhizosphere on physics-ensemble simulations are identified using two different methods: the natural selection and Tukey's test. This study attempts to answer the following questions: 1) what is the relative contribution of precipitation-forcing uncertainty to the overall uncertainty range of Noah-MP simulations at those sites as compared to that at a more moisture and densely vegetated site; 2) what are the most sensitive physical parameterization for those sites; 3) can we identify the parameterizations that need to be improved? The investigation was conducted by evaluating simulated seasonal evolution of soil temperature, soilmoisture, surface heat fluxes through a number of Noah-MP ensemble simulations.

SMOS Soil Moisture Data Assimilation in the NASA Land Information System: Impact on LSM Initialization and NWP Forecasts

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley

2015-01-01

Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.

A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States

NASA Astrophysics Data System (ADS)

Ma, Ning; Niu, Guo-Yue; Xia, Youlong; Cai, Xitian; Zhang, Yinsheng; Ma, Yaoming; Fang, Yuanhao

2017-11-01

Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating Rn but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

NASA Astrophysics Data System (ADS)

Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

2016-11-01

With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Ingwersen, Joachim; Wizemann, Hans-Dieter; Warrach-Sagi, Kirsten; Attinger, Sabine; Streck, Thilo; Wulmeyer, Volker

2014-05-01

Interactions between the soil, the vegetation, and the atmospheric boundary layer require close attention when predicting water fluxes in the hydrogeosystem, agricultural systems, weather and climate. However, land-surface schemes used in large scale models continue to show deficits in consistently simulating fluxes of water and energy from the subsurface through vegetation layers to the atmosphere. In this study, the multi-physics version of the Noah land-surface model (Noah-MP) was used to identify the processes, which are most crucial for a simultaneous simulation of water and heat fluxes between land-surface and the lower atmosphere. Comprehensive field data sets of latent and sensible heat fluxes, ground heat flux, soil moisture, and leaf area index from two contrasting field sites in South-West Germany are used to assess the accuracy of simulations. It is shown that an adequate representation of vegetation-related processes is the most important control for a consistent simulation of energy and water fluxes in the soil-plant-atmosphere system. In particular, using a newly implemented sub-module to simulate root growth dynamics has enhanced the performance of Noah-MP at both field sites. We conclude that further advances in the representation of leaf area dynamics and root/soil moisture interactions are the most promising starting points for improving the simulation of feedbacks between the sub-soil, land-surface and atmosphere in fully-coupled hydrological and atmospheric models.

Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2

NASA Astrophysics Data System (ADS)

Saha, Subodh Kumar; Sujith, K.; Pokhrel, Samir; Chaudhari, Hemantkumar S.; Hazra, Anupam

2017-03-01

The Noah version 2.7.1 is a moderately complex land surface model (LSM), with a single layer snowpack, combined with vegetation and underlying soil layer. Many previous studies have pointed out biases in the simulation of snow, which may hinder the skill of a forecasting system coupled with the Noah. In order to improve the simulation of snow by the Noah, a multilayer snow scheme (up to a maximum of six layers) is introduced. As Noah is the land surface component of the Climate Forecast System version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP), the modified Noah is also coupled with the CFSv2. The offline LSM shows large improvements in the simulation of snow depth, snow water equivalent (SWE), and snow cover area during snow season (October to June). CFSv2 with the modified Noah reveals a dramatic improvements in the simulation of snow depth and 2 m air temperature and moderate improvements in SWE. As suggested in the previous diagnostic and sensitivity study, improvements in the simulation of snow by CFSv2 have lead to the reduction in dry bias over the Indian subcontinent (by a maximum of 2 mm d-1). The multilayer snow scheme shows promising results in the simulation of snow as well as Indian summer monsoon rainfall and hence this development may be the part of the future version of the CFS.

Simulation of boundary layer trajectory dispersion sensitivity to soil moisture conditions: MM5 and noah-based investigation

USDA-ARS?s Scientific Manuscript database

The sensitivity of trajectories from experiments in which volumetric values of soil moisture were changed with respect to control values were analyzed during three different synoptic episodes in June 2006. The MM5 and Noah land surface models were used to simulate the response of the planetary boun...

Improved NLDAS-2 Noah-simulated Hydrometeorological Products with an Interim Run

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Youlong; Peter-Lidard, Christa; Huang, Maoyi

2015-02-28

In NLDAS-2 Noah simulation, the NLDAS team introduced an intermediate fix suggested by Slater et al. (2007) and Livneh et al. (2010) to reduce large sublimation. The fix is used to constraint surface exchange coefficient (CH) using CH =CHoriginal x max (1.0-RiB/0.5, 0.05) when atmospheric boundary layer is stable. RiB is Richardson number. In NLDAS-2 Noah version, this fix was used for all stable cases including snow-free grid cells. In this study, we simply applied this fix to the grid cells in which both stable atmospheric boundary layer and snow exist simultaneously excluding the snow-free grid cells as we recognizemore » that the fix constraint in NLDAS-2 is too strong. We make a 31-year (1979-2009) Noah NLDAS-2 interim (NoahI) run. We use observed streamflow, evapotranspiration, land surface temperature, soil temperature, and ground heat flux to evaluate the results simulated from NoahI and make the reasonable comparison with those simulated from NLDAS-2 Noah (Xia et al., 2012). The results show that NoahI has the same performance as Noah does for snow water equivalent simulation. However, NoahI significantly improved the other hydrometeorological products’ simulation as described above when compared to Noah and the observations. This simple modification is being installed to the next Noah version. The hydrometeorological products simulated from NoahI will be staged on NCEP public server for the public in future.« less

Distributed Application of the Unified Noah LSM with Hydrologic Flow Routing on an Appalachian Headwater Basin

NASA Astrophysics Data System (ADS)

Garcia, M.; Kumar, S.; Gochis, D.; Yates, D.; McHenry, J.; Burnet, T.; Coats, C.; Condrey, J.

2006-05-01

Collaboration between scientists at UMBC-GEST and NASA-GSFC, the NCAR Research Applications Laboratory (RAL), and Baron Advanced Meteorological Services (BAMS), has produced a modeling framework for the application of traditional land surface models (LSMs) in a distributed hydrologic system which can be used for diagnosis and prediction of routed stream discharge hydrographs. This collaboration is oriented on near-term system implementation across Romania for flood and flash-flood analyses and forecasting as part of the World Bank-funded Destructive Waters Abatement (DESWAT) program. Meteorological forcing from surface observations, model analyses and numerical forecasts are employed in the NASA-GSFC Land Information System (LIS) to drive the Unified Noah LSM with Noah-Distributed components, stream network delineation and routing schemes original to this work. The Unified Noah LSM is the outgrowth of a joint modeling effort between several research partners including NCAR, the NOAA National Center for Environmental Prediction (NCEP), and the Air Force Weather Agency (AFWA). At NCAR, hydrologically-oriented extensions to the Noah LSM have been developed for LSM applications in a distributed domain in order to address the lateral redistribution of soil moisture by surface and subsurface flow processes. These advancements have been integrated into the NASA-GSFC Land Information System (LIS) and coupled with an original framework for hydraulic channel network definition and specification, linkages with the Noah-Distributed overland and subsurface flow framework, and distributed cell- to-cell (or link-node) hydraulic routing. This poster presents an overview of the system components and their organization, as well as results of the first U.S. case study performed with this system under various configurations. The case study simulated precipitation events over a headwater basin in the southern Appalachian Mountains in October 2005 following the landfall of Tropical Storm Tammy in South Carolina. These events followed on a long dry period in the region, lending to the demonstration of watershed response to strong precipitation forcing under nearly ideal and easily-specified initial conditions. The results presented here will compare simulated versus observed streamflow conditions at various locations in the test watershed using a selection of routing methods.

Understanding the Impact of Ground Water Treatment and Evapotranspiration Parameterizations in the NCEP Climate Forecast System (CFS) on Warm Season Predictions

NASA Astrophysics Data System (ADS)

Ek, M. B.; Yang, R.

2016-12-01

Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at sub-seasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both the ocean and land surface. The critical importance of ocean has been recognized, where the ocean indices have been used in a variety of climate applications. In contrast, the impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate. The Noah Land Surface Model (LSM) is the land component of NCEP CFS version 2 (CFSv2) used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the Penman-Monteith equation, which takes into account the solar radiation, relative humidity, air temperature, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range, and also potentially misrepresents the soil moisture memory effects at seasonal time scales. To overcome the limitation, an unconfined aquifer is attached to the bottom of the soil to allow the water table to move freely up and down. In addition, in conjunction with the water table, an alternative Ball-Berry photosynthesis-based evaporation parameterization is examined to evaluate the impact from using a different evaporation control methodology. Focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are carried out for the two years using an enhanced version of CFSv2, where the atmospheric component of the CFSv2 is coupled to the Noah Multiple-Parameterization (Noah-MP) land model. The Noah-MP has different options for ground water and evaporation control parameterizations. The differences will be presented and results will be discussed.

Basin-scale assessment of the land surface energy budget in the National Centers for Environmental Prediction operational and research NLDAS-2 systems

NASA Astrophysics Data System (ADS)

Xia, Youlong; Cosgrove, Brian A.; Mitchell, Kenneth E.; Peters-Lidard, Christa D.; Ek, Michael B.; Kumar, Sujay; Mocko, David; Wei, Helin

2016-01-01

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15% for mean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Basin-Scale Assessment of the Land Surface Energy Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

NASA Technical Reports Server (NTRS)

Xia, Youlong; Peters-Lidard, Christa D.; Cosgrove, Brian A.; Mitchell, Kenneth E.; Peters-Lidard, Christa; Ek, Michael B.; Kumar, Sujay V.; Mocko, David M.; Wei, Helin

2015-01-01

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15%formean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Comparing potential recharge estimates from three Land Surface Models across the Western US

PubMed Central

NIRAULA, REWATI; MEIXNER, THOMAS; AJAMI, HOORI; RODELL, MATTHEW; GOCHIS, DAVID; CASTRO, CHRISTOPHER L.

2018-01-01

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01–15% for Mosaic, 3.2–42% for Noah, and 6.7–31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions. PMID:29618845

A warm-season comparison of WRF coupled to the CLM4.0, Noah-MP, and Bucket hydrology land surface schemes over the central USA

NASA Astrophysics Data System (ADS)

Van Den Broeke, Matthew S.; Kalin, Andrew; Alavez, Jose Abraham Torres; Oglesby, Robert; Hu, Qi

2017-11-01

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA.

Development of a hybrid 3-D hydrological model to simulate hillslopes and the regional unconfined aquifer system in Earth system models

NASA Astrophysics Data System (ADS)

Hazenberg, P.; Broxton, P. D.; Brunke, M.; Gochis, D.; Niu, G. Y.; Pelletier, J. D.; Troch, P. A. A.; Zeng, X.

2015-12-01

The terrestrial hydrological system, including surface and subsurface water, is an essential component of the Earth's climate system. Over the past few decades, land surface modelers have built one-dimensional (1D) models resolving the vertical flow of water through the soil column for use in Earth system models (ESMs). These models generally have a relatively coarse model grid size (~25-100 km) and only account for sub-grid lateral hydrological variations using simple parameterization schemes. At the same time, hydrologists have developed detailed high-resolution (~0.1-10 km grid size) three dimensional (3D) models and showed the importance of accounting for the vertical and lateral redistribution of surface and subsurface water on soil moisture, the surface energy balance and ecosystem dynamics on these smaller scales. However, computational constraints have limited the implementation of the high-resolution models for continental and global scale applications. The current work presents a hybrid-3D hydrological approach is presented, where the 1D vertical soil column model (available in many ESMs) is coupled with a high-resolution lateral flow model (h2D) to simulate subsurface flow and overland flow. H2D accounts for both local-scale hillslope and regional-scale unconfined aquifer responses (i.e. riparian zone and wetlands). This approach was shown to give comparable results as those obtained by an explicit 3D Richards model for the subsurface, but improves runtime efficiency considerably. The h3D approach is implemented for the Delaware river basin, where Noah-MP land surface model (LSM) is used to calculated vertical energy and water exchanges with the atmosphere using a 10km grid resolution. Noah-MP was coupled within the WRF-Hydro infrastructure with the lateral 1km grid resolution h2D model, for which the average depth-to-bedrock, hillslope width function and soil parameters were estimated from digital datasets. The ability of this h3D approach to simulate the hydrological dynamics of the Delaware River basin will be assessed by comparing the model results (both hydrological performance and numerical efficiency) with the standard setup of the NOAH-MP model and a high-resolution (1km) version of NOAH-MP, which also explicitly accounts for lateral subsurface and overland flow.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes

NASA Astrophysics Data System (ADS)

Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias

2015-04-01

Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.

Contrastive Analysis of Meteorological Element Effect Simulated by parameterization schemes Land Surface Process of Noah and CLM4 over the Yellow River Source Region

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wen, X.

2017-12-01

The Yellow River source region is situated in the northeast Tibetan Plateau, which is considered as a global climate change hot-spot and one of the most sensitive areas in terms of response to global warming in view of its fragile ecosystem. This region plays an irreplaceable role for downstream water supply of The Yellow River because of its unique topography and variable climate. The water energy cycle processes of the Yellow River source Region from July to September in 2015 were simulated by using the WRF mesoscale numerical model. The two groups respectively used Noah and CLM4 parameterization schemes of land surface process. Based on the observation data of GLDAS data set, ground automatic weather station and Zoige plateau wetland ecosystem research station, the simulated values of near surface meteorological elements and surface energy parameters of two different schemes were compared. The results showed that the daily variations about meteorological factors in Zoige station in September were simulated quite well by the model. The correlation coefficient between the simulated temperature and humidity of the CLM scheme were 0.88 and 0.83, the RMSE were 1.94 ° and 9.97%, and the deviation Bias were 0.04 ° and 3.30%, which was closer to the observation data than the Noah scheme. The correlation coefficients of net radiation, surface heat flux, upward short wave and upward longwave radiation were respectively 0.86, 0.81, 0.84 and 0.88, which corresponded better than the observation data. The sensible heat flux and latent heat flux distribution of the Noah scheme corresponded quite well to GLDAS. the distribution and magnitude of 2m relative humidity and soil moisture were closer to surface observation data because the CLM scheme described the photosynthesis and evapotranspiration of land surface vegetation more rationally. The simulating abilities of precipitation and downward longwave radiation need to be improved. This study provides a theoretical basis for the numerical simulation of water energy cycle in the source region over the Yellow River basin.

Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

NASA Astrophysics Data System (ADS)

Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

2015-12-01

Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow observations in the large watershed to simulations using the terrain and channel routing when Noah-MP is run within the WRF-Hydro modeling framework, with the goals of validating the rainfall-runoff partitioning and translating the spatiotemporal mountain processes into improvements in streamflow predictions.

Validation of Noah-simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Youlong; Ek, Michael; Sheffield, Justin

2013-02-25

Soil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate long-term land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North-American Land Data Assimilation (NLDAS) Phase 2 (NLDAS-2) has generated 31-years (1979-2009) of simulated hourly soil temperature data with a spatial resolution of 1/8o. This dataset has not been comprehensively evaluated to date. Thus, the ultimate purpose of the presentmore » work is to assess Noah-simulated soil temperature for different soil depths and timescales. We used long-term (1979-2001) observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0-10 cm, 10-40 cm, 40-100 cm) for annual and monthly timescales. We used short-term (1997-1999) observed soil temperature from 72 Oklahoma Mesonet stations to validate simulated soil temperatures for three soil layers and for daily and hourly timescales. The results showed that the Noah land surface model (Noah LSM) generally matches observed soil temperature well for different soil layers and timescales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season due to small downward longwave radiation and issues related to model parameters.« less

Evaluation of weather research and forecasting model parameterizations under sea-breeze conditions in a North Sea coastal environment

NASA Astrophysics Data System (ADS)

Salvador, Nadir; Reis, Neyval Costa; Santos, Jane Meri; Albuquerque, Taciana Toledo de Almeida; Loriato, Ayres Geraldo; Delbarre, Hervé; Augustin, Patrick; Sokolov, Anton; Moreira, Davidson Martins

2016-12-01

Three atmospheric boundary layer (ABL) schemes and two land surface models that are used in the Weather Research and Forecasting (WRF) model, version 3.4.1, were evaluated with numerical simulations by using data from the north coast of France (Dunkerque). The ABL schemes YSU (Yonsei University), ACM2 (Asymmetric Convective Model version 2), and MYJ (Mellor-Yamada-Janjic) were combined with two land surface models, Noah and RUC (Rapid Update Cycle), in order to determine the performances under sea-breeze conditions. Particular attention is given in the determination of the thermal internal boundary layer (TIBL), which is very important in air pollution scenarios. The other physics parameterizations used in the model were consistent for all simulations. The predictions of the sea-breeze dynamics output from the WRF model were compared with observations taken from sonic detection and ranging, light detection and ranging systems and a meteorological surface station to verify that the model had reasonable accuracy in predicting the behavior of local circulations. The temporal comparisons of the vertical and horizontal wind speeds and wind directions predicted by the WRF model showed that all runs detected the passage of the sea-breeze front. However, except for the combination of MYJ and Noah, all runs had a time delay compared with the frontal passage measured by the instruments. The proposed study shows that the synoptic wind attenuated the intensity and penetration of the sea breeze. This provided changes in the vertical mixing in a short period of time and on soil temperature that could not be detected by the WRF model simulations with the computational grid used. Additionally, among the tested schemes, the combination of the localclosure MYJ scheme with the land surface Noah scheme was able to produce the most accurate ABL height compared with observations, and it was also able to capture the TIBL.

How important is getting the land surface energy exchange correct in WRF for wind energy forecasting?

NASA Astrophysics Data System (ADS)

Wharton, S.; Simpson, M.; Osuna, J. L.; Newman, J. F.; Biraud, S.

2013-12-01

Wind power forecasting is plagued with difficulties in accurately predicting the occurrence and intensity of atmospheric conditions at the heights spanned by industrial-scale turbines (~ 40 to 200 m above ground level). Better simulation of the relevant physics would enable operational practices such as integration of large fractions of wind power into power grids, scheduling maintenance on wind energy facilities, and deciding design criteria based on complex loads for next-generation turbines and siting. Accurately simulating the surface energy processes in numerical models may be critically important for wind energy forecasting as energy exchange at the surface strongly drives atmospheric mixing (i.e., stability) in the lower layers of the planetary boundary layer (PBL), which in turn largely determines wind shear and turbulence at heights found in the turbine rotor-disk. We hypothesize that simulating accurate a surface-atmosphere energy coupling should lead to more accurate predictions of wind speed and turbulence at heights within the turbine rotor-disk. Here, we tested 10 different land surface model configurations in the Weather Research and Forecasting (WRF) model including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes to flux tower measurements, (2) the accuracy of forecasted wind speeds to observations at rotor-disk heights, and (3) the sensitivity of forecasting hub-height rotor disk wind speed to the choice of land surface model. WRF was run for four, two-week periods covering both summer and winter periods over the Southern Great Plains ARM site in Oklahoma. Continuous measurements of surface energy fluxes and lidar-based wind speed, direction and turbulence were also available. The SGP ARM site provided an ideal location for this evaluation as it centrally located in the wind-rich Great Plains and multi-MW wind farms are rapidly expanding in the area. We found significant differences in simulated wind speeds at rotor-disk heights from WRF which indicated, in part, the sensitivity of lower PBL winds to surface energy exchange. We also found significant differences in energy partitioning between sensible heat and latent energy depending on choice of land surface model. Overall, the most consistent, accurate model results were produced using Noah-MP. Noah-MP was most accurate at simulating energy fluxes and wind shear. Hub-height wind speed, however, was predicted with most accuracy with Pleim-Xiu. This suggests that simulating wind shear in the surface layer is consistent with accurately simulating surface energy exchange while the exact magnitudes of wind speed may be more strongly influenced by the PBL dynamics. As the nation is working towards a 20% wind energy goal by 2030, increasing the accuracy of wind forecasting at rotor-disk heights becomes more important considering that utilities require wind farms to estimate their power generation 24 to 36 hours ahead and face penalties for inaccuracies in those forecasts.

Numerical simulations of island-scale airflow over Maui and the Maui vortex under summer trade wind conditions

Treesearch

DaNa L. Carlis; Yi-Leng Chen; Vernon R. Morris

2010-01-01

The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) coupled with the Noah land surface model (LSM) is employed to simulate island-scale airflow and circulations over Maui County, Hawaii, under summer trade wind conditions, during July–August 2005. The model forecasts are validated by surface observations with good agreement.

Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model

NASA Astrophysics Data System (ADS)

Hong, Seungbum

Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.

Changes in the lower boundary condition of water fluxes in the NOAH land surface scheme

NASA Astrophysics Data System (ADS)

Lohmann, D.; Peters-Lidard, C. D.

2002-05-01

One problem with current land surface schemes (LSS) used in weather prediction and climate models is their inabilty to reproduce streamflow in large river basins. This can be attributed to the weak representation of their upper (infiltration) and lower (baseflow) boundary conditions in their water balance / transport equations. Operational (traditional) hydrological models, which operate on the same spatial scale as a LSS, on the other hand, are able to reproduce streamflow time series. Their infiltration and baseflow equations are often empirically based and therefore have been neglected by the LSS community. It must be argued that we need to include a better representation of long time scales (as represented by groundwater and baseflow) into the current LSS to make valuable predictions of streamflow and water resources. This talk concentrates on the lower boundary condition of water fluxes within LSS. It reviews briefly previous attempts to incorporate groundwater and more realistic lower boundary conditions into LSS and summarizes the effect on the runoff (baseflow) production time scales as compared to currently used lower boundary conditions in LSS. The NOAH - LSM in the LDAS and DMIP setting is used to introduce a simplified groundwater model, based on the linearized Boussinesq equation, and the TOPMODEL. The NOAH - LSM will be coupled to a linear routing model to investigate the effects of the new lower boundary condition on the water balance (in particular, streamflow) in small to medium sized catchments in the LDAS / DMIP domain.

Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.

2014-01-01

As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model (LSM) simulations and includes an Ensemble Kalman Filter for conducting land surface DA. SPoRT has added a module to read, quality-control and bias-correct swaths of Level II SMOS soil moisture retrievals prior to assimilation within LIS. The impact of SMOS DA is being tested using the Noah LSM. Experiments are being conducted to examine the impacts of SMOS soil moisture DA on the resulting LISNoah fields and subsequent NWP simulations using the Weather Research and Forecasting (WRF) model initialized with LIS-Noah output. LIS-Noah soil moisture will be validated against in situ observations from Texas A&M's North American Soil Moisture Database to reveal the impact and possible improvement in soil moisture trends through DA. WRF model NWP case studies will test the impacts of DA on the simulated near-surface and boundary-layer environments, and precipitation during both quiescent and disturbed weather scenarios. Emphasis will be placed on cases with large analysis increments, especially due to contributions from regional irrigation patterns that are not represented by precipitation input in the baseline LIS-Noah run. This poster presentation will describe the soil moisture DA methodology and highlight LIS-Noah and WRF simulation results with and without assimilation.

Multi-model perspectives and inter-comparison of soil moisture and evapotranspiration in East Africa—an application of Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS)

NASA Astrophysics Data System (ADS)

Pervez, M. S.; McNally, A.; Arsenault, K. R.

2017-12-01

Convergence of evidence from different agro-hydrologic sources is particularly important for drought monitoring in data sparse regions. In Africa, a combination of remote sensing and land surface modeling experiments are used to evaluate past, present and future drought conditions. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) routinely simulates daily soil moisture, evapotranspiration (ET) and other variables over Africa using multiple models and inputs. We found that Noah 3.3, Variable Infiltration Capacity (VIC) 4.1.2, and Catchment Land Surface Model based FLDAS simulations of monthly soil moisture percentile maps captured concurrent drought and water surplus episodes effectively over East Africa. However, the results are sensitive to selection of land surface model and hydrometeorological forcings. We seek to identify sources of uncertainty (input, model, parameter) to eventually improve the accuracy of FLDAS outputs. In absence of in situ data, previous work used European Space Agency Climate Change Initiative Soil Moisture (CCI-SM) data measured from merged active-passive microwave remote sensing to evaluate FLDAS soil moisture, and found that during the high rainfall months of April-May and November-December Noah-based soil moisture correlate well with CCI-SM over the Greater Horn of Africa region. We have found good correlations (r>0.6) for FLDAS Noah 3.3 ET anomalies and Operational Simplified Surface Energy Balance (SSEBop) ET over East Africa. Recently, SSEBop ET estimates (version 4) were improved by implementing a land surface temperature correction factor. We re-evaluate the correlations between FLDAS ET and version 4 SSEBop ET. To further investigate the reasons for differences between models we evaluate FLDAS soil moisture with Advanced Scatterometer and SMAP soil moisture and FLDAS outputs with MODIS and AVHRR normalized difference vegetation index. By exploring longer historic time series and near-real time products we will be aiding convergence of evidence for better understanding of historic drought, improved monitoring and forecasting, and better understanding of uncertainties of water availability estimation over Africa

Global terrestrial water storage connectivity revealed using complex climate network analyses

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Noah Pflaum | NREL

Science.gov Websites

| 303-384-7527 Noah joined NREL in 2017 after having worked as a consulting building energy analyst. His to smooth the integration of building energy modeling into the building design process. Noah applies a variety of analytical techniques to solve problems associated with building performance as they

Subsurface Thermal and Hydrological Changes Between a Forested and a Clear-Cut Site in the Oregon Cascades: Observations and Models

NASA Astrophysics Data System (ADS)

Davis, M. G.; Harris, R. N.; Chapman, D. S.

2013-12-01

We report a comparison of temperature and related observations between a set of paired meteorological stations at the Soapgrass Mountain site, Santiam Pass, Cascades Mountains, Oregon, USA. This site contains two separate meteorological towers; one under the old-growth coniferous forest canopy and the other in a nearby forest opening that was clear cut. The open area has warmer air and soil temperatures and receives greater amounts of incoming radiation. These conditions are contrasted with the muted conditions under the forest canopy. A comparison of the sites shows that between 2000 and 2004, differences in air temperature decrease from 1.7 °C to 1.1 °C. Ground temperature differences are nearly cut in half in the leaf litter from 2.8 °C to 1.5 °C over the same time period. We link this change directly to the change in incoming radiation, with an observed decrease from 295 μmol m-2 sec-1 to 233 μmol m-2 sec-1, that is a result of the forest regrowth at the open area site. Subsurface temperatures are reproducible at the open area site using the Noah land surface model, but larger discrepancies exist at the mature forest site. At the mature forest site, the incoming solar radiation is too low to reproduce the observations using the Noah land surface model. Using the incoming solar radiation from the open area allows for much better agreement between the Noah model results and the observations.

Soil Parameters for Representing a Karst Geologic Terrain in the Noah Land-Surface Model over Tennessee and Kentucky

NASA Astrophysics Data System (ADS)

Sullivan, Z.; Fan, X.

2015-12-01

Currently, the Noah Land-Surface Model (Noah-LSM) coupled with the Weather Research and Forecasting (WRF) model does not have a representation of the physical behavior of a karst terrain found in a large area of Tennessee and Kentucky and 25% of land area worldwide. The soluble nature of the bedrock within a karst geologic terrains allows for the formation of caverns, joints, fissures, sinkholes, and underground streams which affect the hydrological behavior of the region. The Highland Rim of Tennessee and the Pennyroyal Plateau and Bluegrass region of Kentucky make up a larger karst area known as the Interior Low Plateau. The highly weathered upper portion of the karst terrain, known as the epikarst, allows for more rapid transport of water through the system. For this study, hydrological aspects, such as bedrock porosity and the hydraulic conductivity, were chosen within this region in order to determine the most representative subsurface parameters for the Noah-LSM. These values along with the use of similar proxy values were chosen to calculate and represent the remaining eight parameters within the SOILPARM.TBL for the WRF model. Hydraulic conductivity values show a variation ranging from around 10-7 and 10-5 ms-1 for the karst bedrock within this region. A sand and clay soil type was used along with bedrock parameters to determine an average soil parameter type for the epikarst bedrock located within this region. Results from this study show parameters for an epikarst bedrock type displaying higher water transport through the system, similar to that of a sandy soil type with a water retention similar to that of a loam type soil. The physical nature of epikarst may lead to a decrease in latent heat values over this region and increase sensible heat values. This, in turn, may effect boundary layer growth which could lead to convective development. Future modeling work can be conducted using these values by way of coupling the soil parameters with the karst regions of the Tennessee/Kentucky area.

Snow Radiance Data Assimilation over High Mountain Asia Using the NASA Land Information System and a Well-Trained Support Vector Machine

NASA Astrophysics Data System (ADS)

Kwon, Y.; Forman, B. A.; Yoon, Y.; Kumar, S.

2017-12-01

High Mountain Asia (HMA) has been progressively losing ice and snow in recent decades, which could negatively impact regional water supply and native ecosystems. One goal of this study is to characterize the spatiotemporal variability of snow (and ice) across the HMA region. In addition, modeled snow water equivalent (SWE) estimates will be enhanced through the assimilation of passive microwave brightness temperatures (TB) collected by the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) as part of a radiance assimilation system. The radiance assimilation framework includes the NASA Land Information System (LIS) in conjunction with a well-trained support vector machine (SVM) that acts as the observation operator. The Noah Land Surface Model with multi-parameterization options (Noah-MP) is used as the prior model for simulating snow dynamics. Noah-MP is forced by meteorological fields from the NASA Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) atmospheric reanalysis for the periods 01 Sep. 2002 to 01 Sep. 2011. The radiance assimilation system requires two separate phases: 1) training and 2) assimilation. During the training phase, a nonlinear SVM is generated for three different AMSR-E frequencies - 10.65, 18.7, and 36.5 GHz - at both vertical and horizontal polarization. The trained SVM is then used to predict TB during the assimilation phase. An ensemble Kalman filter will be used to condition the model on AMSR-E brightness temperatures not used during SVM training. The performance of the Noah-MP (with and without radiance assimilation) will be assessed via comparison to in-situ measurements, remotely-sensing geophysical retrievals, and other reanalysis products.

Green Infrastructure in Kansas City

EPA Science Inventory

We use the state-of-the-art WRF-CMAQ coupled model to simulate the likely effects of a GI implementation strategy in Kansas City, MO/KS on regional meteorology and air quality changes. Two different land surface schemes (Pleim-Xiu and Noah) were implemented to characterize the di...

Global Land Data Assimilation System (GLDAS) Products, Services and Application from NASA Hydrology Data and Information Services Center (HDISC)

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Beaudoing, Hiroko K.; Rodell, matthew; Teng, William L.; Vollmer, Bruce E.

2009-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. Users can search the products through keywords and perform on-the-fly spatial and parameter subsetting and format conversion of selected data. More advanced visualization, access and analysis capabilities will be available in the future. The long term GLDAS data are used to develop climatology of water cycle components and to explore the teleconnections of droughts and pluvial.

Global Land Data Assimilation System (GLDAS) Products from NASA Hydrology Data and Information Services Center (HDISC)

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Hrubiak, Patricia; Kato, Hiroko; Rodell, Matthew; Teng, William L.; Vollmer, Bruce E.

2008-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. New data formats (e.g., netCDF), temporal averaging and spatial subsetting will be available in the future. The HDISC has the capability to support more hydrology data products and more advanced analysis tools. The goal is to develop HDISC as a data and services portal that supports weather and climate forecast, and water and energy cycle research.

Numerical Study on the Stomatal Responses to Dry-Hot Wind Episodes and Its Effects on Land-Atmosphere Interactions.

PubMed

Wang, Shu; Zheng, Hui; Liu, Shuhua; Miao, Yucong; Li, Jing

2016-01-01

The wheat production in midland China is under serious threat by frequent Dry-Hot Wind (DHW) episodes with high temperature, low moisture and specific wind as well as intensive heat transfer and evapotranspiration. The numerical simulations of these episodes are important for monitoring grain yield and estimating agricultural water demand. However, uncertainties still remain despite that enormous experiments and modeling studies have been conducted concerning this issue, due to either inaccurate synoptic situation derived from mesoscale weather models or unrealistic parameterizations of stomatal physiology in land surface models. Hereby, we investigated the synoptic characteristics of DHW with widely-used mesoscale model Weather Research and Forecasting (WRF) and the effects of leaf physiology on surface evapotranspiration by comparing two land surface models: The Noah land surface model, and Peking University Land Model (PKULM) with stomata processes included. Results show that the WRF model could well replicate the synoptic situations of DHW. Two types of DHW were identified: (1) prevailing heated dry wind stream forces the formation of DHW along with intense sensible heating and (2) dry adiabatic processes overflowing mountains. Under both situations, the PKULM can reasonably model the stomatal closure phenomena, which significantly decreases both evapotranspiration and net ecosystem exchange of canopy, while these phenomena cannot be resolved in the Noah simulations. Therefore, our findings suggest that the WRF-PKULM coupled method may be a more reliable tool to investigate and forecast DHW as well as be instructive to crop models.

Numerical Study on the Stomatal Responses to Dry-Hot Wind Episodes and Its Effects on Land-Atmosphere Interactions

PubMed Central

Zheng, Hui; Liu, Shuhua; Miao, Yucong; Li, Jing

2016-01-01

The wheat production in midland China is under serious threat by frequent Dry-Hot Wind (DHW) episodes with high temperature, low moisture and specific wind as well as intensive heat transfer and evapotranspiration. The numerical simulations of these episodes are important for monitoring grain yield and estimating agricultural water demand. However, uncertainties still remain despite that enormous experiments and modeling studies have been conducted concerning this issue, due to either inaccurate synoptic situation derived from mesoscale weather models or unrealistic parameterizations of stomatal physiology in land surface models. Hereby, we investigated the synoptic characteristics of DHW with widely-used mesoscale model Weather Research and Forecasting (WRF) and the effects of leaf physiology on surface evapotranspiration by comparing two land surface models: The Noah land surface model, and Peking University Land Model (PKULM) with stomata processes included. Results show that the WRF model could well replicate the synoptic situations of DHW. Two types of DHW were identified: (1) prevailing heated dry wind stream forces the formation of DHW along with intense sensible heating and (2) dry adiabatic processes overflowing mountains. Under both situations, the PKULM can reasonably model the stomatal closure phenomena, which significantly decreases both evapotranspiration and net ecosystem exchange of canopy, while these phenomena cannot be resolved in the Noah simulations. Therefore, our findings suggest that the WRF-PKULM coupled method may be a more reliable tool to investigate and forecast DHW as well as be instructive to crop models. PMID:27648943

Expansion of the Real-time Sport-land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.

2014-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has been running a real-time version of the Land Information System (LIS) since summer 2010 (hereafter, SPoRTLIS). The real-time SPoRT-LIS runs the Noah land surface model (LSM) in an offline capacity apart from a numerical weather prediction model, using input atmospheric and precipitation analyses (i.e., "forcings") to drive the Noah LSM integration at 3-km resolution. Its objectives are to (1) produce local-scale information about the soil state for NOAA/National Weather Service (NWS) situational awareness applications such as drought monitoring and assessing flood potential, and (2) provide land surface initialization fields for local modeling initiatives. The current domain extent has been limited by the input atmospheric analyses that drive the Noah LSM integration within SPoRT-LIS, specifically the National Centers for Environmental Prediction (NCEP) Stage IV precipitation analyses. Due to the nature of the geographical edges of the Stage IV precipitation grid and its limitations in the western U.S., the SPoRT-LIS was originally confined to a domain fully nested within the Stage IV grid, over the southeastern half of the Conterminous United States (CONUS). In order to expand the real-time SPoRT-LIS to a full CONUS domain, alternative precipitation forcing datasets were explored in year-long, offline comparison runs of the Noah LSM. Based on results of these comparison simulations, we chose to implement the radar/gauge-based precipitation analyses from the National Severe Storms Laboratory as a replacement to the Stage IV product. The Multi-Radar Multi-Sensor (MRMS; formerly known as the National Mosaic and multi-sensor Quantitative precipitation estimate) product has full CONUS coverage at higher-resolution, thereby providing better coverage and greater detail than that of the Stage IV product. This paper will describe the expanded/upgraded SPoRT-LIS, present comparisons between the original and upgraded SPoRT-LIS, and discuss the path forward for future collaboration opportunities with SPoRT partners in the NWS.

Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

NASA Astrophysics Data System (ADS)

Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

2017-12-01

An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

Implementing dynamic root optimization in Noah-MP for simulating phreatophytic root water uptake

USDA-ARS?s Scientific Manuscript database

Plants are known to adjust their root systems to adapt to changing subsurface water conditions. However, most current land surface models (LSMs) use a prescribed, static root profile, which cuts off the interactions between soil moisture and root dynamics. In this paper, we implemented an optimality...

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Molthan, Andrew L.; Zavodsky, Bradley T.; Rozumalski, Robert A.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS). In last year's NWA abstract on this topic, the suite of SPoRT products supported in the STRC EMS was presented, which includes a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This abstract and companion presentation describes recent upgrades made to the SST and GVF composites, as well as the real-time LIS runs. The Great Lakes sea-ice product is unchanged from 2011. The SPoRT SST composite product has been expanded geographically and as a result, the resolution has been coarsened from 1 km to 2 km to accommodate the larger domain. The expanded domain covers much of the northern hemisphere from eastern Asia to western Europe (0 N to 80 N latitude and 150 E to 10 E longitude). In addition, the NESDIS POES-GOES product was added to fill in gaps caused by the Moderate Resolution Imaging Spectroradiometer (MODIS) being unable to sense in cloudy regions, replacing the recently-lost Advanced Microwave Scanning Radiometer for EOS with negligible change to product fidelity. The SST product now runs twice per day for Terra and Aqua combined data collections from 0000 to 1200 UTC and from 1200 to 0000 UTC, with valid analysis times at 0600 and 1800 UTC. The twice-daily compositing technique reduces the overall latency of the previous version while still representing the diurnal cycle characteristics. The SST composites are available at approximately four hours after the end of each collection period (i.e. 1600 UTC for the nighttime analysis and 0400 UTC for the daytime analysis). The real-time MODIS GVF composite has only received minor updates in the past year. The domain was expanded slightly to extend further west, north, and east to improve coverage over parts of southern Canada. Minor adjustments were also made to the manner in which GVF is calculated from the distribution of maximum Normalized Difference Vegetation Index from MODIS. The presentation will highlight some examples of the substantial inter-annual change in GVF that occurred from 2010 to 2011 in the U.S. Southern Plains as a result of the summer 2011 drought, and the early vegetation green up across the eastern U.S. due to the very warm conditions in March 2012. Finally, the SPoRT LIS runs the operational Noah land surface model (LSM) in real time over much of the eastern half of the CONUS. The Noah LSM is continually cycled in real time, uncoupled to any model, and driven by operational atmospheric analyses over a long-term, multi-year integration. The LIS-Noah provides the STRC EMS with high-resolution (3 km) LSM initialization data that are in equilibrium with the operational analysis forcing. The Noah LSM within the SPoRT LIS has been upgraded from version 2.7.1 to version 3.2, which has improved look-up table attributes for several land surface quantities. The surface albedo field is now being adjusted based on the input real-time MODIS GVF, thereby improving the net radiation. Also, the LIS-Noah now uses the newer MODIS-based land use classification scheme (i.e. the International Biosphere-Geosphere Programme [IGBP]) that has a better depiction of urban corridors in areas where urban sprawl has occurred. STRC EMS users interested in initializing their LSM fields with high-resolution SPoRT LIS data should set up their model domain with the MODIS-IGBP 20-class land use database and select Noah as the LSM.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2011-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours

Infusion of SMAP Data into Offline and Coupled Models: Evaluation, Calibration, and Assimilation

NASA Astrophysics Data System (ADS)

Lawston, P.; Santanello, J. A., Jr.; Dennis, E. J.; Kumar, S.

2017-12-01

The impact of the land surface on the water and energy cycle is modulated by its coupling to the planetary boundary layer (PBL), and begins at the local scale. A core component of the local land-atmosphere coupling (LoCo) effort requires understanding the `links in the chain' between soil moisture and precipitation, most notably through surface heat fluxes and PBL evolution. To date, broader (i.e. global) application of LoCo diagnostics has been limited by observational data requirements of the coupled system (and in particular, soil moisture) that are typically only met during localized, short-term field campaigns. SMAP offers, for the first time, the ability to map high quality, near-surface soil moisture globally every few days at a spatial resolution comparable to current modeling efforts. As a result, there are numerous potential avenues for SMAP model-data fusion that can be explored in the context of improving understanding of L-A interaction and NWP. In this study, we assess multiple points of intersection of SMAP products with offline and coupled models and evaluate impacts using process-level diagnostics. Results will inform upon the importance of high-resolution soil moisture mapping for improved coupled prediction and model development, as well as reconciling differences in modeled, retrieved, and measured soil moisture. Specifically, NASA model (LIS, NU-WRF) and observation (SMAP, NLDAS-2) products are combined with in-situ standard and IOP measurements (soil moisture, flux, and radiosonde) over the ARM-SGP. An array of land surface model spinups (via LIS-Noah) are performed with varying atmospheric forcing, greenness fraction, and soil layering permutations. Calibration of LIS-Noah soil hydraulic parameters is then performed using an array of in-situ soil moisture and flux and SMAP products. In addition, SMAP assimilation is performed in LIS-Noah both at the scale of the observation (36 and 9km) and the model grid (1km). The focus is on the consistency in calibrated parameters, impact of soil drydown dynamics and soil layers, and terrestrial (soil moisture-flux) coupling. The impacts of these various spinup runs and initialization of NU-WRF coupled forecasts then follows with a focus on weather (ambient, PBL, and precipitation) using LoCo metrics.

Simulation of semi-arid biomass plantations and irrigation using the WRF-NOAH model - a comparison with observations from Israel

NASA Astrophysics Data System (ADS)

Branch, O.; Warrach-Sagi, K.; Wulfmeyer, V.; Cohen, S.

2014-05-01

A 10 × 10 km irrigated biomass plantation was simulated in an arid region of Israel to simulate diurnal energy balances during the summer of 2012 (JJA). The goal is to examine daytime horizontal flux gradients between plantation and desert. Simulations were carried out within the coupled WRF-NOAH atmosphere/land surface model. MODIS land surface data was adjusted by prescribing tailored land surface and soil/plant parameters, and by adding a controllable sub-surface irrigation scheme to NOAH. Two model cases studies were compared - Impact and Control. Impact simulates the irrigated plantation. Control simulates the existing land surface, where the predominant land surface is bare desert soil. Central to the study is parameter validation against land surface observations from a desert site and from a 400 ha Simmondsia chinensis (jojoba) plantation. Control was validated with desert observations, and Impact with Jojoba observations. Model evapotranspiration was validated with two Penman-Monteith estimates based on the observations. Control simulates daytime desert conditions with a maximum deviation for surface 2 m air temperatures (T2) of 0.2 °C, vapour pressure deficit (VPD) of 0.25 hPa, wind speed (U) of 0.5 m s-1, surface radiation (Rn) of 25 W m-2, soil heat flux (G) of 30 W m-2 and 5 cm soil temperatures (ST5) of 1.5 °C. Impact simulates irrigated vegetation conditions with a maximum deviation for T2 of 1-1.5 °C, VPD of 0.5 hPa, U of 0.5 m s-1, Rn of 50 W m-5, G of 40 W m-2 and ST5 of 2 °C. Latent heat curves in Impact correspond closely with Penman-Monteith estimates, and magnitudes of 160 W m-2 over the plantation are usual. Sensible heat fluxes, are around 450 W m-2 and are at least 100-110 W m-2 higher than the surrounding desert. This surplus is driven by reduced albedo and high surface resistance, and demonstrates that high evaporation rates may not occur over Jojoba if irrigation is optimized. Furthermore, increased daytime T2 over plantations highlight the need for hourly as well as daily mean statistics. Daily mean statistics alone may imply an overall cooling effect due to surplus nocturnal cooling, when in fact a daytime warming effect is observed.

Verification of High Resolution Soil Moisture and Latent Heat in Germany

NASA Astrophysics Data System (ADS)

Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.

2012-12-01

Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were obtained by closing the water balance over major river basins in Germany. Simulated soil moisture and latent heat flux were also evaluated at several eddy covariance sites in Germany. Comparison of monthly soil moisture and latent heat fields obtained with both models over Germany exhibited significant differences, which are mainly attributed to the subgrid variability of key model parameters such as porosity and aerodynamic resistance. Comparison of soil moisture fields obtained with WRF/Noah-MP and mHM forced with grided metereological observations (German Meteorological Service) showed that the differences between both models are mainly due to a combination of precipitation bias and different soil texture resolution. However, EOF analyses indicate that CORDEX results start recovering structures due to soil and vegetation properties. This experiment clearly highlighted the importance of hyper resolution input data to address these challenge. High resolution mHM simulations also indicate that the parametric uncertainty of land surface models is significant, and should not be neglected if a model is to be employed for application at regional scales, e.g. for drought monitoring.

Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Beaudoing, Hiroko; Rodell, Matthew; Teng, BIll; Vollmer, Bruce

2008-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface Models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of NASA Goddard Earth Sciences Data and Information Services Center (GESDISC).

Climate Prediction Center - United States Drought Information

Science.gov Websites

• Crop Moisture Indices • Soil Moisture Percentiles (based on NLDAS) • Standardized Runoff Index (based /Minimum • Mean Surface Hydrology (based on NLDAS) • Total Soil Moisture • Total SM Change • MOSAIC Soil Moisture Profile • NOAH Soil Moisture Profile • NOAH Soil T Profile • Evaporation • E-P Â

Comparison and Assessment of Three Advanced Land Surface Models in Simulating Terrestrial Water Storage Components over the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Youlong; Mocko, David; Huang, Maoyi

2017-03-01

In preparation for next generation North American Land Data Assimilation System (NLDAS), 3 three advanced land surface models (CLM4.0, Noah-MP, and CLSM-F2.5) were run from 1979 4 to 2014 within the NLDAS-based framework. Monthly total water storage anomaly (TWSA) and 5 its individual water storage components were evaluated against satellite-based and in situ 6 observations, and reference reanalysis products at basin-wide and statewide scales. In general, all 7 three models are able to reasonably capture the monthly and interannual variability and 8 magnitudes for TWSA. However, contributions of the anomalies of individual water 9 components to TWSA are very dependentmore » on the model and basin. A major contributor to the 10 TWSA is the anomaly of total column soil moisture content (SMCA) for CLM4.0 and Noah-MP 11 or groundwater storage anomaly (GWSA) for CLSM-F2.5 although other components such as 12 the anomaly of snow water equivalent (SWEA) also play some role. For each individual water 13 storage component, the models are able to capture broad features such as monthly and 14 interannual variability. However, there are large inter-model differences and quantitative 15 uncertainties in this study. Therefore, it should be thought of as a preliminary synthesis and 16 analysis.« less

Calibration of Noah soil hydraulic property parameters using surface soil moisture from SMOS and basin-wide in situ observations

USDA-ARS?s Scientific Manuscript database

Soil hydraulic properties can be retrieved from physical sampling of soil, via surveys, but this is time consuming and only as accurate as the scale of the sample. Remote sensing provides an opportunity to get pertinent soil properties at large scales, which is very useful for large scale modeling....

Development and Evaluation of a Cloud-Gap-Filled MODIS Daily Snow-Cover Product

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Foster, James L.; Kumar, Sujay V.

2010-01-01

The utility of the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. We describe a cloud-gap-filled (CGF) daily snowcover map using a simple algorithm to track cloud persistence, to account for the uncertainty created by the age of the snow observation. Developed from the 0.050 resolution climate-modeling grid daily snow-cover product, MOD10C1, each grid cell of the CGF map provides a cloud-persistence count (CPC) that tells whether the current or a prior day was used to make the snow decision. Percentage of grid cells "observable" is shown to increase dramatically when prior days are considered. The effectiveness of the CGF product is evaluated by conducting a suite of data assimilation experiments using the community Noah land surface model in the NASA Land Information System (LIS) framework. The Noah model forecasts of snow conditions, such as snow-water equivalent (SWE), are updated based on the observations of snow cover which are obtained either from the MOD1 OC1 standard product or the new CGF product. The assimilation integrations using the CGF maps provide domain averaged bias improvement of -11 %, whereas such improvement using the standard MOD1 OC1 maps is -3%. These improvements suggest that the Noah model underestimates SWE and snow depth fields, and that the assimilation integrations contribute to correcting this systematic error. We conclude that the gap-filling strategy is an effective approach for increasing cloud-free observations of snow cover.

Modeled effects of irrigation on surface climate in the Heihe River Basin, Northwest China

NASA Astrophysics Data System (ADS)

Zhang, Xuezhen; Xiong, Zhe; Tang, Qiuhong

2017-08-01

In Northwest China, water originates from the mountain area and is largely used for irrigation agriculture in the middle reaches. This study investigates the local and remote impact of irrigation on regional climate in the Heihe River Basin, the second largest inland river basin in Northwest China. An irrigation scheme was developed and incorporated into the Weather Research and Forecasting (WRF) model with the Noah-MP land surface scheme (WRF/Noah-MP). The effects of irrigation is assessed by comparing the model simulations with and without consideration of irrigation (hereafter, IRRG and NATU simulations, respectively) for five growth seasons (May to September) from 2009 to 2013. As consequences of irrigation, daily mean temperature decreased by 1.7°C and humidity increased by 2.3 g kg-1 (corresponding to 38.5%) over irrigated area. The temperature and humidity of IRRG simulation matched well with the observations, whereas NATU simulation overestimated temperature and underestimated humidity over irrigated area. The effects on temperature and humidity are generally small outside the irrigated area. The cooling and wetting effects have opposing impacts on convective precipitation, resulting in a negligible change in localized precipitation over irrigated area. However, irrigation may induce water vapor convergence and enhance precipitation remotely in the southeastern portion of the Heihe River Basin.

The Effect of Soil Hydraulic Properties vs. Soil Texture in Land Surface Models

NASA Technical Reports Server (NTRS)

Gutmann, E. D.; Small, E. E.

2005-01-01

This study focuses on the effect of Soil Hydraulic Property (SHP) selection on modeled surface fluxes following a rain storm in a semi-arid environment. SHPs are often defined based on a Soil Texture Class (STC). To examine the effectiveness of this approach, the Noah land surface model was run with each of 1306 soils in a large SHP database. Within most STCs, the outputs have a range of 350 W/m2 for latent and sensible heat fluxes, and 8K for surface temperature. The average difference between STC median values is only 100 W/m2 for latent and sensible heat. It is concluded that STC explains 5-15% of the variance in model outputs and should not be used to determine SHPs.

Upper Blue Nile basin water budget from a multi-model perspective

NASA Astrophysics Data System (ADS)

Jung, Hahn Chul; Getirana, Augusto; Policelli, Frederick; McNally, Amy; Arsenault, Kristi R.; Kumar, Sujay; Tadesse, Tsegaye; Peters-Lidard, Christa D.

2017-12-01

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Emergent properties of climate-vegetation feedbacks in the North American Monsoon Macrosystem

NASA Astrophysics Data System (ADS)

Mathias, A.; Niu, G.; Zeng, X.

2012-12-01

The ability of ecosystems to adapt naturally to climate change and associated disturbances (e.g. wildfires, spread of invasive species) is greatly affected by the stability of feedback interactions between climate and vegetation. In order to study climate-vegetation interactions, such as CO2 and H2O exchange in the North American Monsoon System (NAMS), we plan to couple a community land surface model (NoahMP or CLM) used in regional climate models (WRF) with an individual based, spatially explicit vegetation model (ECOTONE). Individual based modeling makes it possible to link individual plant traits with properties of plant communities. Community properties, such as species composition and species distribution arise from dynamic interactions of individual plants with each other, and with their environment. Plants interact with each other through intra- and interspecific competition for resources (H2O, nitrogen), and the outcome of these interactions depends on the properties of the plant community and the environment itself. In turn, the environment is affected by the resulting change in community structure, which may have an impact on the drivers of climate change. First, we performed sensitivity tests of ECOTONE to assess its ability to reproduce vegetation distribution in the NAMS. We compared the land surface model and ECOTONE with regard to their capability to accurately simulate soil moisture, CO2 flux and above ground biomass. For evaluating the models we used the eddy-correlation sensible and latent heat fluxes, CO2 flux and observations of other climate and environmental variables (e.g. soil temperature and moisture) from the Santa Rita experimental range. The model intercomparison helped us understand the advantages and disadvantages of each model, providing us guidance for coupling the community land surface model (NoahMP or CLM) with ECOTONE.

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Evaluation of LIS-based Soil Moisture and Evapotranspiration in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Jung, H. C.; Kang, D. H.; Kim, E. J.; Yoon, Y.; Kumar, S.; Peters-Lidard, C. D.; Baeck, S. H.; Hwang, E.; Chae, H.

2017-12-01

K-water is the South Korean national water agency. It is the government-funded private agency for water resource development that provides both civil and industrial water in S. Korea. K-water is interested in exploring how earth remote sensing and modeling can help their tasks. In this context, the NASA Land Information System (LIS) is implemented to simulate land surface processes in the Korean Peninsula. The Noah land surface model with Multi-Parameterization, version 3.6 (Noah-MP) is used to reproduce the water budget variables on a 1 km spatial resolution grid with a daily temporal resolution. The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) datasets is used to force the system. The rainfall data are spatially downscaled from high resolution WorldClim precipitation climatology. The other meteorological inputs (i.e. air temperature, humidity, pressure, winds, radiation) are also downscaled by statistical methods (i.e. lapse-rate, slope-aspect). Additional model experiments are conducted with local rainfall datasets and soil maps to replace the downscaled MERRA-2 precipitation field and the hybrid STATSGO/FAO soil texture, respectively. For the evaluation of model performance, daily soil moisture and evapotranspiration measurements at several stations are compared to the LIS-based outputs. This study demonstrates that application of NASA's LIS can enhance drought and flood prediction capabilities in South Asia and Korea.

Conservation priorities when species interact: the Noah's Ark metaphor revisited.

PubMed

Courtois, Pierre; Figuieres, Charles; Mulier, Chloé

2014-01-01

This note incorporates ecological interactions into the Noah's Ark problem. In doing so, we arrive at a general model for ranking in situ conservation projects accounting for species interrelations and provide an operational cost-effectiveness method for the selection of best preserving diversity projects under a limited budget constraint.

Noah's Ark-Red Cross Foundation: a Swedish model.

PubMed

Florence, M E

1993-01-01

During the Spring of 1991, the author spent many weeks at the Noah's Ark-Red Cross Foundation, a support service for HIV infected persons, and their families and friends, located in Stockholm, Sweden. The purpose was to study, through interviews, observation and participation, the foundation's interactive model in order to discover what makes it work and share that knowledge with other professionals. The Noah's Ark Model consists of three spheres of activity: service, including reception services and the volunteer programme; information and education, including the Hot Line and the Newsletter; and counselling and support, including the guest house. Staff from each area interact freely with and participate in the activities of other areas. The foundation also utilizes the services of carefully trained volunteers. This use of volunteers makes it unique in Sweden. It is the dedication and flexibility of the staff and volunteers that make this model work. The report of the study follows.

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

Using WRF-Urban to Assess Summertime Air Conditioning Electric Loads and Their Impacts on Urban Weather in Beijing

NASA Astrophysics Data System (ADS)

Xu, Xiaoyu; Chen, Fei; Shen, Shuanghe; Miao, Shiguang; Barlage, Michael; Guo, Wenli; Mahalov, Alex

2018-03-01

The air conditioning (AC) electric loads and their impacts on local weather over Beijing during a 5 day heat wave event in 2010 are investigated by using the Weather Research and Forecasting (WRF) model, in which the Noah land surface model with multiparameterization options (Noah-MP) is coupled to the multilayer Building Effect Parameterization and Building Energy Model (BEP+BEM). Compared to the legacy Noah scheme coupled to BEP+BEM, this modeling system shows a better performance, decreasing the root-mean-square error of 2 m air temperature to 1.9°C for urban stations. The simulated AC electric loads in suburban and rural districts are significantly improved by introducing the urban class-dependent building cooled fraction. Analysis reveals that the observed AC electric loads in each district are characterized by a common double peak at 3 p.m. and at 9 p.m. local standard time, and the incorporation of more realistic AC working schedules helps reproduce the evening peak. Waste heat from AC systems has a smaller effect ( 1°C) on the afternoon 2 m air temperature than the evening one (1.5 2.4°C) if AC systems work for 24 h and vent sensible waste heat into air. Influences of AC systems can only reach up to 400 m above the ground for the evening air temperature and humidity due to a shallower urban boundary layer than daytime. Spatially varying maps of AC working schedules and the ratio of sensible to latent waste heat release are critical for correctly simulating the cooling electric loads and capturing the thermal stratification of urban boundary layer.

Conservation Priorities when Species Interact: The Noah's Ark Metaphor Revisited

PubMed Central

Courtois, Pierre; Figuieres, Charles; Mulier, Chloé

2014-01-01

This note incorporates ecological interactions into the Noah's Ark problem. In doing so, we arrive at a general model for ranking in situ conservation projects accounting for species interrelations and provide an operational cost-effectiveness method for the selection of best preserving diversity projects under a limited budget constraint. PMID:25181514

Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

NASA Astrophysics Data System (ADS)

Nair, A. S.; Indu, J.

2017-12-01

Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.

Soil moisture from ground-based networks and the North American Land Data Assimilation System Phase 2 Model: Are the right values somewhere in between?

NASA Astrophysics Data System (ADS)

Caldwell, T. G.; Scanlon, B. R.; Long, D.; Young, M.

2013-12-01

Soil moisture is the most enigmatic component of the water balance; nonetheless, it is inherently tied to every component of the hydrologic cycle, affecting the partitioning of both water and energy at the land surface. However, our ability to assess soil water storage capacity and status through measurement or modeling is challenged by error and scale. Soil moisture is as difficult to measure as it is to model, yet land surface models and remote sensing products require some means of validation. Here we compare the three major soil moisture monitoring networks across the US, including the USDA Soil Climate Assessment Network (SCAN), NOAA Climate Reference Network (USCRN), and Cosmic Ray Soil Moisture Observing System (COSMOS) to the soil moisture simulated using the North American Land Data Assimilation System (NLDAS) Phase 2. NLDAS runs in near real-time on a 0.125° (12 km) grid over the US, producing ensemble model outputs of surface fluxes and storage. We focus primarily on soil water storage (SWS) in the upper 0-0.1 m zone from the Noah Land Surface Model and secondarily on the effects of error propagation from atmospheric forcing and soil parameterization. No scaling of the observational data was attempted. We simply compared the extracted time series at the nearest grid center from NLDAS and assessed the results by standard model statistics including root mean square error (RMSE) and mean bias estimate (MBE) of the collocated ground station. Observed and modeled data were compared at both hourly and daily mean coordinated universal time steps. In all, ~300 stations were used for 2012. SCAN sites were found to be particularly troublesome at 5- and 10-cm depths. SWS at 163 SCAN sites departed significantly from Noah with a mean R2 of 0.38 × 0.0.23, a mean RMSE of 14.9 mm with a MBE of -13.5 mm. SWS at 111 USCRN sites has a mean R2 of 0.53 × 0.20, a mean RMSE of 8.2 mm with a MBE of -3.7 mm relative to Noah. Finally, 62 COSMOS sites, the instrument with the largest measurement footprint (0.03 km2), we calculated a mean R2 of 0.53 × 0.21, a mean RMSE of 9.7 mm with a MBE of -0.3 mm. Forcing errors and textural misclassifications correlate well with model biases, indicating that scale and structural errors are equally present in NLDAS. Scaling issues aside, these confounding errors make cal/val missions, such as NASA's upcoming Soil Moisture Active Passive (SMAP) mission, problematic without significant quality control and maintenance of for our monitoring networks. Land surface models, such as NLDAS-2, may provide valuable insight into our soil moisture data and somewhere in between the real values likely exist.

Evaluation of Remote Sensing and Hydrological Model Based Soil Moisture Datasets in Drought Perspective

NASA Astrophysics Data System (ADS)

Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.

2017-12-01

Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.

Evaluation of snowmelt simulation in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Jin, Jiming; Wen, Lijuan

2012-05-01

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

NASA Astrophysics Data System (ADS)

Fang, H.; Kato, H.; Rodell, M.; Teng, W. L.; Vollmer, B. E.

2008-12-01

The Global Land Data Assimilation System (GLDAS) has been generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products, simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current GLDAS data hosted at HDISC include a set of 1.0° data products, covering 1979 to the present, from the four models and a 0.25° data product, covering 2000 to the present, from the Noah model. In addition to the basic anonymous ftp data downloading, users can avail themselves of several advanced data search and downloading services, such as Mirador and OPeNDAP. Mirador is a Google-based search tool that provides keywords searching, on-the-fly spatial and parameter subsetting of selected data. OPeNDAP (Open-source Project for a Network Data Access Protocol) enables remote OPeNDAP clients to access OPeNDAP served data regardless of local storage format. Additional data services to be available in the near future from HDISC include (1) on-the-fly converter of GLDAS to NetCDF and binary data formats; (2) temporal aggregation of GLDAS files; and (3) Giovanni, an online visualization and analysis tool that provides a simple way to visualize, analyze, and access vast amounts of data without having to download the data.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

NASA Technical Reports Server (NTRS)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

NASA Technical Reports Server (NTRS)

Xia, Youlong; Cosgrove, Brian A.; Mitchell, Kenneth E.; Peters-Lidard, Christa D.; Ek, Michael B.; Brewer, Michael; Mocko, David; Kumar, Sujay V.; Wei, Helin; Meng, Jesse;

Evaluation and intercomparison of five major dry deposition ...

EPA Pesticide Factsheets

Dry deposition of various pollutants needs to be quantified in air quality monitoring networks as well as in chemical transport models. The inferential method is the most commonly used approach in which the dry deposition velocity (Vd) is empirically parameterized as a function of meteorological and biological conditions and pollutant species’ chemical properties. Earlier model intercomparison studies suggested that existing dry deposition algorithms produce quite different Vd values, e.g., up to a factor of 2 for monthly to annual average values for ozone, and sulfur and nitrogen species (Flechard et al., 2011; Schwede et al., 2011; Wu et al., 2011). To further evaluate model discrepancies using available flux data, this study compared the five dry deposition algorithms commonly used in North America and evaluated the models using five-year Vd(O3) and Vd(SO2) data generated from concentration gradient measurements above a temperate mixed forest in Canada. The five algorithms include: (1) the one used in the Canadian Air and Precipitation Monitoring Network (CAPMoN) and several Canadian air quality models based on Zhang et al. (2003), (2) the one used in the US Clean Air Status and Trends Network (CASTNET) based on Meyers et al. (1998), (3) the one used in the Community Multiscale Air Quality (CMAQ) model described in Pleim and Ran (2011), (4) the Noah land surface model coupled with a photosynthesis-based Gas Exchange Model (Noah-GEM) described in Wu et a

Smithsonian's NOAHS: Keepers of the Ark. The New Explorers.

ERIC Educational Resources Information Center

Sheldon, Louisa; McCoy, Barbara; Leong, Kirsten; Wallace, Gwendolyn; Barwick, Allen; Reymund, Trudi

The New Opportunities in Animal Health Sciences (NOAHS) Center at the National Zoological Park in Washington, DC. is dedicated to expanding understanding of the biological factors, including the critical role of biodiversity, that influence animal survival. This set of activities includes a description of NOAHS and the NOAHS mission, and letters…

The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.

SMAP Data Assimilation at NASA SPoRT

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2016-01-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

Improved methods for estimating local terrestrial water dynamics from GRACE in the Northern High Plains

NASA Astrophysics Data System (ADS)

Seyoum, Wondwosen M.; Milewski, Adam M.

2017-12-01

Investigating terrestrial water cycle dynamics is vital for understanding the recent climatic variability and human impacts in the hydrologic cycle. In this study, a downscaling approach was developed and tested, to improve the applicability of terrestrial water storage (TWS) anomaly data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission for understanding local terrestrial water cycle dynamics in the Northern High Plains region. A non-parametric, artificial neural network (ANN)-based model, was utilized to downscale GRACE data by integrating it with hydrological variables (e.g. soil moisture) derived from satellite and land surface model data. The downscaling model, constructed through calibration and sensitivity analysis, was used to estimate TWS anomaly for watersheds ranging from 5000 to 20,000 km2 in the study area. The downscaled water storage anomaly data were evaluated using water storage data derived from an (1) integrated hydrologic model, (2) land surface model (e.g. Noah), and (3) storage anomalies calculated from in-situ groundwater level measurements. Results demonstrate the ANN predicts monthly TWS anomaly within the uncertainty (conservative error estimate = 34 mm) for most of the watersheds. Seasonal derived groundwater storage anomaly (GWSA) from the ANN correlated well (r = ∼0.85) with GWSAs calculated from in-situ groundwater level measurements for a watershed size as small as 6000 km2. ANN downscaled TWSA matches closely with Noah-based TWSA compared to standard GRACE extracted TWSA at a local scale. Moreover, the ANN-downscaled change in TWS replicated the water storage variability resulting from the combined effect of climatic and human impacts (e.g. abstraction). The implications of utilizing finer resolution GRACE data for improving local and regional water resources management decisions and applications are clear, particularly in areas lacking in-situ hydrologic monitoring networks.

Uniting Mandelbrot’s Noah and Joseph Effects in Toy Models of Natural Hazard Time Series

NASA Astrophysics Data System (ADS)

Credgington, D.; Watkins, N. W.; Chapman, S. C.; Rosenberg, S. J.; Sanchez, R.

2009-12-01

The forecasting of extreme events is a highly topical, cross-disciplinary problem. One aspect which is potentially tractable even when the events themselves are stochastic is the probability of a “burst” of a given size and duration, defined as the area between a time series and a constant threshold. Many natural time series depart from the simplest, Brownian, case and in the 1960s Mandelbrot developed the use of fractals to describe these departures. In particular he proposed two kinds of fractal model to capture the way in which natural data is often persistent in time (his “Joseph effect”, common in hydrology and exemplified by fractional Brownian motion) and/or prone to heavy tailed jumps (the “Noah effect”, typical of economic index time series, for which he gave Levy flights as an examplar). Much of the earlier modelling, however, has emphasised one of the Noah and Joseph parameters (the tail exponent mu and one derived from the temporal behaviour such as power spectral beta) at the other one's expense. I will describe work [1] in which we applied a simple self-affine stable model-linear fractional stable motion (LFSM)-which unifies both effects to better describe natural data, in this case from space physics. I will show how we have resolved some contradictions seen in earlier work, where purely Joseph or Noah descriptions had been sought. I will also show recent work [2] using numerical simulations of LFSM and simple analytic scaling arguments to study the problem of the area between a fractional Levy model time series and a threshold. [1] Watkins et al, Space Science Reviews [2005] [2] Watkins et al, Physical Review E [2009

Behavior of Agricultural water users induced hydro-climatic cycle change in Heihe River Basin, in the northwest of china

NASA Astrophysics Data System (ADS)

Wu, F.; Deng, X.; Cai, X.; Zhang, X.; Zhang, Q.

2017-12-01

Water allocation unbalance is the most important driving force of ecological degradation in the Heihe River Basin, where it seems the lifeblood of environment and human society. Water commute complex and frequent in soil, atmosphere, surface and ground face. The balance analysis of Water's transformation based on the WRF (Weather Research Forecasting) and SWAT (Soil and Water Assessment Tool) simulations, puts forward the application of land governance in arid and semi-arid region. In this study, we designed an irrigation scheme using local field experiences and incorporated the irrigation scheme into WRF/Noah-MP model. Then, to test the effects of irrigation scheme on performance of WRF/Noah-MP model, we carried out two simulations with the Heihe watershed, Northwest China, as a case study area. Firstly, the irrigation simulation is meanly about 860 mm across all of 671 cropland grid cells within the Heihe watershed and gradually increases from about 500 mm nearby the foot of Qilian Mountain to the maximum about 1500 mm in the middle and lower reach of Heihe River. Both of regional mean value and spatial heterogeneity are close to ground measurements. Secondly, the irrigation simulation dramatically reduced the mean bias of specified humidity to -0.47 g kg-1 (accounting for 6.0% of observation) and RMSE of temperature to 0.47 °C, respectively, since the irrigation enhanced the surface latent heat and weakened sensible heat to atmosphere. Thirdly, Across the 8 agricultural sites, the correlation coefficient and RMSE increased from 0.75 to 0.80. Finally, we found the surface runoff will increase by 0.46% with SWAT model at irrigation months. Therefore, the irrigation may led to expansion of cultivated land through transformation from groundwater to surface water at some degree. Water authorities should strengthen the tough water management measures to implement measures of total quantity control and raise the efficiency of water resources.

Comparative stereodynamics in molecule-atom and molecule-molecule rotational energy transfer: NO(A{sup 2}Σ{sup +}) + He and D{sub 2}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luxford, Thomas F. M.; Sharples, Thomas R.; McKendrick, Kenneth G.

2016-08-28

We present a crossed molecular beam scattering study, using velocity-map ion-imaging detection, of state-to-state rotational energy transfer for NO(A{sup 2}Σ{sup +}) in collisions with the kinematically identical colliders He and D{sub 2}. We report differential cross sections and angle-resolved rotational angular momentum polarization moments for transfer of NO(A, v = 0, N = 0, j = 0.5) to NO(A, v = 0, N′ = 3, 5-12) in collisions with He and D{sub 2} at respective average collision energies of 670 cm{sup −1} and 663 cm{sup −1}. Quantum scattering calculations on a literature ab initio potential energy surface for NO(A)-He [J.more » Kłos et al., J. Chem. Phys. 129, 244303 (2008)] yield near-quantitative agreement with the experimental differential scattering cross sections and good agreement with the rotational polarization moments. This confirms that the Kłos et al. potential is accurate within the experimental collisional energy range. Comparison of the experimental results for NO(A) + D{sub 2} and He collisions provides information on the hitherto unknown NO(A)-D{sub 2} potential energy surface. The similarities in the measured scattering dynamics of NO(A) imply that the general form of the NO(A)-D{sub 2} potential must be similar to that calculated for NO(A)-He. A consistent trend for the rotational rainbow maximum in the differential cross sections for NO(A) + D{sub 2} to peak at more forward angles than those for NO(A) + He is consistent with the NO(A)-D{sub 2} potential being more anisotropic with respect to NO(A) orientation. No evidence is found in the experimental measurements for coincident rotational excitation of the D{sub 2}, consistent with the potential having low anisotropy with respect to D{sub 2}. The NO(A) + He polarization moments deviate systematically from the predictions of a hard-shell, kinematic-apse scattering model, with larger deviations as N′ increases, which we attribute to the shallow gradient of the anisotropic repulsive NO(A)-He potential energy surface.« less

An Overview of the National Weather Service National Water Model

NASA Astrophysics Data System (ADS)

Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Feng, X.; Karsten, L. R.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.

2016-12-01

The National Weather Service (NWS) Office of Water Prediction (OWP), in conjunction with the National Center for Atmospheric Research (NCAR) and the NWS National Centers for Environmental Prediction (NCEP) recently implemented version 1.0 of the National Water Model (NWM) into operations. This model is an hourly cycling uncoupled analysis and forecast system that provides streamflow for 2.7 million river reaches and other hydrologic information on 1km and 250m grids. It will provide complementary hydrologic guidance at current NWS river forecast locations and significantly expand guidance coverage and type in underserved locations. The core of this system is the NCAR-supported community Weather Research and Forecasting (WRF)-Hydro hydrologic model. It ingests forcing from a variety of sources including Multi-Sensor Multi-Radar (MRMS) radar-gauge observed precipitation data and High Resolution Rapid Refresh (HRRR), Rapid Refresh (RAP), Global Forecast System (GFS) and Climate Forecast System (CFS) forecast data. WRF-Hydro is configured to use the Noah-Multi Parameterization (Noah-MP) Land Surface Model (LSM) to simulate land surface processes. Separate water routing modules perform diffusive wave surface routing and saturated subsurface flow routing on a 250m grid, and Muskingum-Cunge channel routing down National Hydrogaphy Dataset Plus V2 (NHDPlusV2) stream reaches. River analyses and forecasts are provided across a domain encompassing the Continental United States (CONUS) and hydrologically contributing areas, while land surface output is available on a larger domain that extends beyond the CONUS into Canada and Mexico (roughly from latitude 19N to 58N). The system includes an analysis and assimilation configuration along with three forecast configurations. These include a short-range 15 hour deterministic forecast, a medium-Range 10 day deterministic forecast and a long-range 30 day 16-member ensemble forecast. United Sates Geologic Survey (USGS) streamflow observations are assimilated into the analysis and assimilation configuration, and all four configurations benefit from the inclusion of 1,260 reservoirs. An overview of the National Water Model will be given, along with information on ongoing evaluation activities and plans for future NWM enhancements.

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Expansion of the Real-Time SPoRT-Land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L; White, Kristopher D.

2014-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014.This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations.

A comparison between the effects of artificial land cover and anthropogenic heat on a localized heavy rain event in 2008 in Zoshigaya, Tokyo, Japan

NASA Astrophysics Data System (ADS)

Souma, Kazuyoshi; Tanaka, Kenji; Suetsugi, Tadashi; Sunada, Kengo; Tsuboki, Kazuhisa; Shinoda, Taro; Wang, Yuqing; Sakakibara, Atsushi; Hasegawa, Koichi; Moteki, Qoosaku; Nakakita, Eiichi

2013-10-01

5 August 2008, a localized heavy rainfall event caused a rapid increase in drainpipe discharge, which killed five people working in a drainpipe near Zoshigaya, Tokyo. This study compared the effects of artificial land cover and anthropogenic heat on this localized heavy rainfall event based on three ensemble experiments using a cloud-resolving model that includes realistic urban features. The first experiment CTRL (control) considered realistic land cover and urban features, including artificial land cover, anthropogenic heat, and urban geometry. In the second experiment NOAH (no anthropogenic heat), anthropogenic heat was ignored. In the third experiment NOLC (no land cover), urban heating from artificial land cover was reduced by keeping the urban geometry but with roofs, walls, and roads of artificial land cover replaced by shallow water. The results indicated that both anthropogenic heat and artificial land cover increased the amount of precipitation and that the effect of artificial land cover was larger than that of anthropogenic heat. However, in the middle stage of the precipitation event, the difference between the two effects became small. Weak surface heating in NOAH and NOLC reduced the near-surface air temperature and weakened the convergence of horizontal wind and updraft over the urban areas, resulting in a reduced rainfall amount compared with that in CTRL.

Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Sets

NASA Technical Reports Server (NTRS)

Vollmer, Bruce E.; Rui, Hualan; Mocko, David M.; Teng, William L.; Lei, Guang-Dih

2012-01-01

The North American Land Data Assimilation System (NLDAS) is a collaborative project between NASA GSFC, NOAA, Princeton University, and the University of Washington. NLDAS has created surface meteorological forcing data sets using the best-available observations and reanalyses. The forcing data sets are used to drive four separate land-surface models (LSMs), Mosaic, Noah, VIC, and SAC, to produce data sets of soil moisture, snow, runoff, and surface fluxes. NLDAS hourly data, accessible from the NASA GES DISC Hydrology Data Holdings Portal, http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, are widely used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies of extreme events. More information is available at http://ldas.gsfc.nasa.gov/. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data sets have been recently released by NASA GES DISC.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2018-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm3 cm−3. These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve. PMID:29367795

Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

NASA Astrophysics Data System (ADS)

Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

2016-12-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Berndt, Emily B.; Srikishen, Jayanthi; Zavodsky, Bradley T.

2014-01-01

The NASA SPoRT Center is working to incorporate Suomi-NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land-atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre-frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land-atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real-time product, thereby offering a higher-quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real-time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

National Centers for Environmental Prediction

Science.gov Websites

/ VISION | About EMC EMC > NOAH > IMPLEMENTATION SCHEDULLE Home Operational Products Experimental Data Verification Model Configuration Implementation Schedule Collaborators Documentation FAQ Code

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

NASA Astrophysics Data System (ADS)

Tariku, Tebikachew Betru; Gan, Thian Yew

2018-06-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB.

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

NASA Astrophysics Data System (ADS)

Tariku, Tebikachew Betru; Gan, Thian Yew

2017-08-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB.

Investigating the relationship between climate teleconnection patterns and soil moisture variability in the Rio Grande/Río Bravo del Norte basin using the NOAH land surface model

NASA Astrophysics Data System (ADS)

Khedun, C. P.; Mishra, A. K.; Bolten, J. D.; Giardino, J. R.; Singh, V. P.

2010-12-01

Soil moisture is an important component of the hydrological cycle. Climate variability patterns, such as the Pacific Decadal Oscillation (PDO), El Niño Southern Oscillation (ENSO), and Atlantic Multidecadal Oscillation (AMO) are determining factors on surface water availability and soil moisture. Understanding this complex relationship and the phase and lag times between climate events and soil moisture variability is important for agricultural management and water planning. In this study we look at the effect of these climate teleconnection patterns on the soil moisture across the Rio Grande/Río Bravo del Norte basin. The basin is transboundary between the US and Mexico and has a varied climatology - ranging from snow dominated in its headwaters in Colorado, to an arid and semi-arid region in its middle reach and a tropical climate in the southern section before it discharges into the Gulf of Mexico. Agricultural activities in the US and in northern Mexico are highly dependent on the Rio Grande and are extremely vulnerable to climate extremes. The treaty between the two countries does not address climate related events. The soil moisture is generated using the community NOAH land surface model (LSM). The LSM is a 1-D column model that runs in coupled or uncoupled mode, and it simulates soil moisture, soil temperature, skin temperature, snowpack depth, snow water equivalent, canopy water content, and energy flux and water flux of the surface energy and water balance. The North American Land Data Assimilation Scheme 2 (NLDAS2) is used to drive the model. The model is run for the period 1979 to 2009. The soil moisture output is validated against measured values from the different Soil Climate Analysis Network (SCAN) sites within the basin. The spatial and temporal variability of the modeled soil moisture is then analyzed using marginal entropy to investigate monthly, seasonal, and annual variability. Wavelet transform is used to determine the relation, phase difference, and lag times between climate teleconnection events and soil moisture. The results from this study will help agricultural scientists and water planners in both the US and Mexico in better managing the dwindling water resources of this transboundary basin.

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Understanding Changes in Water Availability in the Rio Grande/Rio Bravo del Norte Basin Under the Influence of Large-Scale Circulation Indices Using the Noah Land Surface Model

NASA Technical Reports Server (NTRS)

Khedun, C. Prakash; Mishra, Ashok K.; Bolten, John D.; Beaudoing, Hiroko K.; Kaiser, Ronald A.; Giardino, J. Richard; Singh, Vijay P.

2012-01-01

Water availability plays an important role in the socio-economic development of a region. It is however, subject to the influence of large-scale circulation indices, resulting in periodic excesses and deficits. An assessment of the degree of correlation between climate indices and water availability, and the quantification of changes with respect to major climate events is important for long-term water resources planning and management, especially in transboundary basins as it can help in conflict avoidance. In this study we first establish the correlation of the Pacific Decadal Oscillation (PDO) and El Nino-Southern Oscillation (ENSO) with gauged precipitation in the Rio Grande basin, and quantify the changes in water availability using runoff generated from the Noah land surface model. Both spatial and temporal variations are noted, with winter and spring being most influenced by conditions in the Pacific Ocean. Negative correlation is observed at the headwaters and positive correlation across the rest of the basin. The influence of individual ENSO events, classified using four different criteria, is also examined. El Ninos (La Ninas) generally cause an increase (decrease) in runoff, but the pattern is not consistent; percentage change in water availability varies across events. Further, positive PDO enhances the effect of El Nino and dampens that of La Nina, but during neutral/transitioning PDO, La Nina dominates meteorological conditions. Long El Ninos have more influence on water availability than short duration high intensity events. We also note that the percentage increase during El Ninos significantly offsets the drought-causing effect of La Ninas.

P69 Using the NASA-Unified WRF to Assess the Impacts of Real-Time Vegetation on Simulations of Severe Weather

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Peters-Lidard, Christa D.

2012-01-01

Since June 2010, the NASA Short-term Prediction Research and Transition (SPoRT; Goodman et al. 2004; Darden et al. 2010; Stano et al. 2012; Fuell et al. 2012) Center has been generating a real-time Normalized Difference Vegetation Index (NDVI) and corresponding Green Vegetation Fraction (GVF) composite based on reflectances from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. This dataset is generated at 0.01 resolution across the Continental United States (CONUS), and updated daily. The goal of producing such a vegetation dataset is to improve over the default climatological GVF dataset in land surface and numerical weather prediction models, in order to have better simulations of heat and moisture exchange between the land surface and the planetary boundary layer. Details on the SPoRT/MODIS vegetation composite algorithm are presented in Case et al. (2011). Vegetation indices such as GVF and Leaf Area Index (LAI) are used by land surface models (LSMs) to represent the horizontal and vertical density of plant vegetation (Gutman and Ignatov 1998), in order to calculate transpiration, interception and radiative shading. Both of these indices are related to the NDVI; however, there is an inherent ambiguity in determining GVF and LAI simultaneously from NDVI, as described in Gutman and Ignatov (1998). One practice is to specify the LAI while allowing the GVF to vary both spatially and temporally, as is done in the Noah LSM (Chen and Dudhia 2001; Ek et al. 2003). Operational versions of Noah within several of the National Centers for Environmental Prediction (NCEP) global and regional modeling systems hold the LAI fixed, while the GVF varies according to a global monthly climatology. This GVF climatology was derived from NDVI data on the NOAA Advanced Very High Resolution Radiometer (AVHRR) polar orbiting satellite, using information from 1985 to 1991 (Gutman and Ignatov 1998; Jiang et al. 2010). Representing data at the mid-point of every month, the climatological dataset is on a grid with 0.144 (16 km) spatial resolution and is distributed with the community WRF model (Ek et al. 2003; Jiang et al. 2010; Skamarock et al. 2008).

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

NASA Technical Reports Server (NTRS)

Long, Di; Yang, Yuting; Yoshihide, Wada; Hong, Yang; Liang, Wei; Chen, Yaning; Yong, Bin; Hou, Aizhong; Wei, Jiangfeng; Chen, Lu

2015-01-01

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

NASA Technical Reports Server (NTRS)

Reichle, R. H.

2010-01-01

Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

Understanding Mesoscale Land-Atmosphere Interactions in Arctic Region

NASA Astrophysics Data System (ADS)

Hong, X.; Wang, S.; Nachamkin, J. E.

2017-12-01

Land-atmosphere interactions in Arctic region are examined using the U.S. Navy Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS©*) with the Noah Land Surface Model (LSM). Initial land surface variables in COAMPS are interpolated from the real-time NASA Land Information System (LIS). The model simulations are configured for three nest grids with 27-9-3 km horizontal resolutions. The simulation period is set for October 2015 with 12-h data assimilation update cycle and 24-h integration length. The results are compared with those simulated without using LSM and evaluated with observations from ONR Sea State R/V Sikuliaq cruise and the North Slope of Alaska (NSA). There are complex soil and vegetation types over the surface for simulation with LSM, compared to without LSM simulation. The results show substantial differences in surface heat fluxes between bulk surface scheme and LSM, which may have an important impact on the sea ice evolution over the Arctic region. Evaluations from station data show surface air temperature and relative humidity have smaller biases for simulation using LSM. Diurnal variation of land surface temperature, which is necessary for physical processes of land-atmosphere, is also better captured than without LSM.

A Comparison of Land Surface Model Soil Hydraulic Properties Estimated by Inverse Modeling and Pedotransfer Functions

NASA Technical Reports Server (NTRS)

Gutmann, Ethan D.; Small, Eric E.

2007-01-01

Soil hydraulic properties (SHPs) regulate the movement of water in the soil. This in turn plays an important role in the water and energy cycles at the land surface. At present, SHPS are commonly defined by a simple pedotransfer function from soil texture class, but SHPs vary more within a texture class than between classes. To examine the impact of using soil texture class to predict SHPS, we run the Noah land surface model for a wide variety of measured SHPs. We find that across a range of vegetation cover (5 - 80% cover) and climates (250 - 900 mm mean annual precipitation), soil texture class only explains 5% of the variance expected from the real distribution of SHPs. We then show that modifying SHPs can drastically improve model performance. We compare two methods of estimating SHPs: (1) inverse method, and (2) soil texture class. Compared to texture class, inverse modeling reduces errors between measured and modeled latent heat flux from 88 to 28 w/m(exp 2). Additionally we find that with increasing vegetation cover the importance of SHPs decreases and that the van Genuchten m parameter becomes less important, while the saturated conductivity becomes more important.

Monitoring of the Spatial Distribution and Temporal Dynamics of the Green Vegetation Fraction of Croplands in Southwest Germany Using High-Resolution RapidEye Satellite Images

NASA Astrophysics Data System (ADS)

Imukova, Kristina; Ingwersen, Joachim; Streck, Thilo

2014-05-01

The green vegetation fraction (GVF) is a key input variable to the evapotranspiration scheme applied in the widely used NOAH land surface model (LSM). In standard applications of the NOAH LSM, the GVF is taken from a global map with a 15 km×15 km resolution. The central objective of the present study was (a) to derive gridded GVF data in a high spatial and temporal resolution from RapidEye images for a region in Southwest Germany, and (b) to improve the representation of the GVF dynamics of croplands in the NOAH LSM for a better simulation of water and energy exchange between land surface and atmosphere. For the region under study we obtained monthly RapidEye satellite images with a resolution 5 m×5 m by the German Aerospace Center (DLR). The images hold five spectral bands: blue, green, red, red-edge and near infrared (NIR). The GVF dynamics were determined based on the Normalized Difference Vegetation Index (NDVI) calculated from the red and near-infrared bands of the satellite images. The satellite GVF data were calibrated and validated against ground truth measurements. Digital colour photographs above the canopy were taken with a boom-mounted digital camera at fifteen permanently marked plots (1 m×1 m). Crops under study were winter wheat, winter rape and silage maize. The GVF was computed based on the red and the green band of the photographs according to Rundquist's method (2002). Based on the obtained calibration scheme GVF maps were derived in a monthly resolution for the region. Our results confirm a linear relationship between GVF and NDVI and demonstrate that it is possible to determine the GVF of croplands from RapidEye images based on a simple two end-member mixing model. Our data highlight the high variability of the GVF in time and space. At the field scale, the GVF was normally distributed with a coefficient of variation of about 32%. Variability was mainly caused by soil heterogeneities and management differences. At the regional scale the GVF showed a bimodal distribution, which could be related to the different cultivation schemes of crops. We suggest to divide croplands according their distinctly different temporal dynamics of the GVF into "early covering - maturing" crops (winter rape, winter wheat, spring barley) and "late covering - non-maturing" crops (sugar beet, silage maize). Based on the achieved results we recommend that simulations with LSM should take into account this differentiation of croplands since it is to be expected that these two crop groups have pronounced differences with regard to energy partitioning at the land surface.

Hydrologic modeling for monitoring water availability in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Harrison, L.; Shukla, S.; Pricope, N. G.; Peters-Lidard, C. D.

2017-12-01

Severe droughts in 2015, 2016 and 2017 in Ethiopia, Southern Africa, and Somalia have negatively impacted agriculture and municipal water supplies resulting in food and water insecurity. Information from remotely sensed data and field reports indicated that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation (FLDAS) accurately tracked both the anomalously low soil moisture, evapotranspiration and runoff conditions. This work presents efforts to more precisely monitor how the water balance responds to water availability deficits (i.e. drought) as estimated by the FLDAS with CHIRPS precipitation, MERRA-2 meteorological forcing and the Noah33 land surface model.Preliminary results indicate that FLDAS streamflow estimates are well correlated with observed streamflow where irrigation and other channel modifications are not present; FLDAS evapotranspiration (ET) is well correlated with ET from the Operational Simplified Surface Energy Balance model (SSEBop) in Eastern and Southern Africa. We then use these results to monitor availability, and explore trends in water supply and demand.

National Centers for Environmental Prediction

Science.gov Websites

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Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.

2017-12-01

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.

SMERGE: A multi-decadal root-zone soil moisture product for CONUS

NASA Astrophysics Data System (ADS)

Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.

2017-12-01

Multi-decadal root-zone soil moisture products are of value for a range of water resource and climate applications. The NASA-funded root-zone soil moisture merging project (SMERGE) seeks to develop such products through the optimal merging of land surface model predictions with surface soil moisture retrievals acquired from multi-sensor remote sensing products. This presentation will describe the creation and validation of a daily, multi-decadal (1979-2015), vertically-integrated (both surface to 40 cm and surface to 100 cm), 0.125-degree root-zone product over the contiguous United States (CONUS). The modeling backbone of the system is based on hourly root-zone soil moisture simulations generated by the Noah model (v3.2) operating within the North American Land Data Assimilation System (NLDAS-2). Remotely-sensed surface soil moisture retrievals are taken from the multi-sensor European Space Agency Climate Change Initiative soil moisture data set (ESA CCI SM). In particular, the talk will detail: 1) the exponential smoothing approach used to convert surface ESA CCI SM retrievals into root-zone soil moisture estimates, 2) the averaging technique applied to merge (temporally-sporadic) remotely-sensed with (continuous) NLDAS-2 land surface model estimates of root-zone soil moisture into the unified SMERGE product, and 3) the validation of the SMERGE product using long-term, ground-based soil moisture datasets available within CONUS.

A comparison of river discharge calculated by using a regional climate model output with different reanalysis datasets in 1980s and 1990s

NASA Astrophysics Data System (ADS)

Ma, X.; Yoshikane, T.; Hara, M.; Adachi, S. A.; Wakazuki, Y.; Kawase, H.; Kimura, F.

2014-12-01

To check the influence of boundary input data on a modeling result, we had a numerical investigation of river discharge by using runoff data derived by a regional climate model with a 4.5-km resolution as input data to a hydrological model. A hindcast experiment, which to reproduce the current climate was carried out for the two decades, 1980s and 1990s. We used the Advanced Research WRF (ARW) (ver. 3.2.1) with a two-way nesting technique and the WRF single-moment 6-class microphysics scheme. Noah-LSM is adopted to simulate the land surface process. The NCEP/NCAR and ERA-Interim 6-hourly reanalysis datasets were used as the lateral boundary condition for the runs, respectively. The output variables used for river discharge simulation from the WRF model were underground runoff and surface runoff. Four rivers (Mogami, Agano, Jinzu and Tone) were selected in this study. The results showed that the characteristic of river discharge in seasonal variation could be represented and there were overestimated compared with measured one.

Quantifying the changes in the High Mountain Asia snow hydrology

NASA Astrophysics Data System (ADS)

Yoon, Y.; Kumar, S.; Mocko, D. M.; Rosenberg, R. I.; Kwon, Y.; Forman, B. A.; Zaitchik, B. F.

2017-12-01

The melting of snow and glaciers in the High Mountain Asia (HMA) provides the water needs of approximately 1.3 billion people in the region. Increasing temperatures have large effects on the hydrologic cycle, influencing snowmelt, snowpack, stream flow, and water runoff, which can impact all aspects of water security, such as water allocation, conservation, efficiency and land-use planning. Most mountain regions, however, remain ungauged without in-situ measurement of precipitation or snowpack due to the complex terrain, and thus it is difficult to understand the regional water balance and assess how it might change in the future. In this study, we focus on characterizing the spatiotemporal patterns of snowpack states and fluxes over the last 30+ years (1980 - present) and assessing the relationship between snowmelt and runoff. The Noah land surface model with multi-parameterization options, version 3.6 (Noah-MP.3.6) in the NASA Land Information System (LIS) is used to establish a high resolution (1 km) modeling environment over the HMA. Combining information from satellite observations and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is used to provide an effective way to develop spatially and temporally continuous estimates of changes. To improve the spatial representativeness of the precipitation field for modeling at 1km resolution, the input field is downscaled using a stochastic downscaling method with the monthly WorldClim data. The other meteorological inputs (e.g., air temperature, humidity, pressure, wind, and downward shortwave and longwave) are corrected for elevation through lapse-rate and slope-aspect methods. Evaluation of the model estimates is presented using satellite-derived data (e.g., MODIS and GRACE) and reanalysis products (e.g., CMC and ERA-interim).

An evaluation of the performance of a WRF multi-physics ensemble for heatwave events over the city of Melbourne in southeast Australia

NASA Astrophysics Data System (ADS)

Imran, H. M.; Kala, J.; Ng, A. W. M.; Muthukumaran, S.

2018-04-01

Appropriate choice of physics options among many physics parameterizations is important when using the Weather Research and Forecasting (WRF) model. The responses of different physics parameterizations of the WRF model may vary due to geographical locations, the application of interest, and the temporal and spatial scales being investigated. Several studies have evaluated the performance of the WRF model in simulating the mean climate and extreme rainfall events for various regions in Australia. However, no study has explicitly evaluated the sensitivity of the WRF model in simulating heatwaves. Therefore, this study evaluates the performance of a WRF multi-physics ensemble that comprises 27 model configurations for a series of heatwave events in Melbourne, Australia. Unlike most previous studies, we not only evaluate temperature, but also wind speed and relative humidity, which are key factors influencing heatwave dynamics. No specific ensemble member for all events explicitly showed the best performance, for all the variables, considering all evaluation metrics. This study also found that the choice of planetary boundary layer (PBL) scheme had largest influence, the radiation scheme had moderate influence, and the microphysics scheme had the least influence on temperature simulations. The PBL and microphysics schemes were found to be more sensitive than the radiation scheme for wind speed and relative humidity. Additionally, the study tested the role of Urban Canopy Model (UCM) and three Land Surface Models (LSMs). Although the UCM did not play significant role, the Noah-LSM showed better performance than the CLM4 and NOAH-MP LSMs in simulating the heatwave events. The study finally identifies an optimal configuration of WRF that will be a useful modelling tool for further investigations of heatwaves in Melbourne. Although our results are invariably region-specific, our results will be useful to WRF users investigating heatwave dynamics elsewhere.

Groundwater Withdrawals under Drought: Reconciling GRACE and Models in the United States High Plains Aquifer

NASA Astrophysics Data System (ADS)

Nie, W.; Zaitchik, B. F.; Kumar, S.; Rodell, M.

2017-12-01

Advanced Land Surface Models (LSM) offer a powerful tool for studying and monitoring hydrological variability. Highly managed systems, however, present a challenge for these models, which typically have simplified or incomplete representations of human water use, if the process is represented at all. GRACE, meanwhile, detects the total change in water storage, including change due to human activities, but does not resolve the source of these changes. Here we examine recent groundwater declines in the US High Plains Aquifer (HPA), a region that is heavily utilized for irrigation and that is also affected by episodic drought. To understand observed decline in groundwater (well observation) and terrestrial water storage (GRACE) during a recent multi-year drought, we modify the Noah-MP LSM to include a groundwater pumping irrigation scheme. To account for seasonal and interannual variability in active irrigated area we apply a monthly time-varying greenness vegetation fraction (GVF) dataset to the model. A set of five experiments were performed to study the impact of irrigation with groundwater withdrawal on the simulated hydrological cycle of the HPA and to assess the importance of time-varying GVF when simulating drought conditions. The results show that including the groundwater pumping irrigation scheme in Noah-MP improves model agreement with GRACE mascon solutions for TWS and well observations of groundwater anomaly in the southern HPA, including Texas and Kansas, and that accounting for time-varying GVF is important for model realism under drought. Results for the HPA in Nebraska are mixed, likely due to misrepresentation of the recharge process. This presentation will highlight the value of the GRACE constraint for model development, present estimates of the relative contribution of climate variability and irrigation to declining TWS in the HPA under drought, and identify opportunities to integrate GRACE-FO with models for water resource monitoring in heavily irrigated regions.

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

NASA Technical Reports Server (NTRS)

Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

2011-01-01

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Measuring and modeling changes in land-atmosphere exchanges and hydrologic response in forests undergoing insect-driven mortality

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Brooks, P. D.; Harpold, A. A.; Ewers, B. E.; Pendall, E.; Barnard, H. R.; Reed, D.; Harley, P. C.; Hu, J.; Biederman, J.

2010-12-01

Given the magnitude and spatial extent of recent forest mortality in the western U.S. there is a pressing need to improve representation of such influences on the exchange of energy, water, biogeochemical and momentum fluxes in land-atmosphere parameterizations coupled to weather and climate models. In this talk we present observational data and model results from a new study aimed at improving understanding the impacts of mountain pine beetle-induced forest mortality in the central Rocky Mountains. Baseline observations and model runs from undisturbed lodgepole pine forest conditions are developed as references against which new observations and model runs from infested stands are compared. We will specifically look at the structure and evolution of sub-canopy energy exchange variables such as shortwave and longwave radiation and sub-canopy turbulence as well as sub-canopy precipitation, sapflow fluxes, canopy-scale fluxes and soil moisture and temperature. In this manner we seek to lay the ground work for evaluating the recent generation of land surface model changes aimed at representing insect-related forest dynamics in the CLM-C/N and Noah land surface models.

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Kuligowski, Robert J.; Langston, Carrie

2013-01-01

The NASA Short ]term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real ]time configuration of the NASA Land Information System (LIS) with the Noah land surface model (LSM). Output from the SPoRT ]LIS run is used to initialize land surface variables for local modeling applications at select National Weather Service (NWS) partner offices, and can be displayed in decision support systems for situational awareness and drought monitoring. The SPoRT ]LIS is run over a domain covering the southern and eastern United States, fully nested within the National Centers for Environmental Prediction Stage IV precipitation analysis grid, which provides precipitation forcing to the offline LIS ]Noah runs. The SPoRT Center seeks to expand the real ]time LIS domain to the entire Continental U.S. (CONUS); however, geographical limitations with the Stage IV analysis product have inhibited this expansion. Therefore, a goal of this study is to test alternative precipitation forcing datasets that can enable the LIS expansion by improving upon the current geographical limitations of the Stage IV product. The four precipitation forcing datasets that are inter ]compared on a 4 ]km resolution CONUS domain include the Stage IV, an experimental GOES quantitative precipitation estimate (QPE) from NESDIS/STAR, the National Mosaic and QPE (NMQ) product from the National Severe Storms Laboratory, and the North American Land Data Assimilation System phase 2 (NLDAS ]2) analyses. The NLDAS ]2 dataset is used as the control run, with each of the other three datasets considered experimental runs compared against the control. The regional strengths, weaknesses, and biases of each precipitation analysis are identified relative to the NLDAS ]2 control in terms of accumulated precipitation pattern and amount, and the impacts on the subsequent LSM spin ]up simulations. The ultimate goal is to identify an alternative precipitation forcing dataset that can best support an expansion of the real ]time SPoRT ]LIS to a domain covering the entire CONUS.

National Climate Assessment - Land Data Assimilation System (NCA-LDAS) Data and Services at NASA GES DISC

NASA Technical Reports Server (NTRS)

Rui, Hualan; Vollmer, Bruce; Teng, Bill; Jasinski, Michael; Mocko, David; Loeser, Carlee; Kempler, Steven

2016-01-01

The National Climate Assessment-Land Data Assimilation System (NCA-LDAS) is an Integrated Terrestrial Water Analysis, and is one of NASAs contributions to the NCA of the United States. The NCA-LDAS has undergone extensive development, including multi-variate assimilation of remotely-sensed water states and anomalies as well as evaluation and verification studies, led by the Goddard Space Flight Centers Hydrological Sciences Laboratory (HSL). The resulting NCA-LDAS data have recently been released to the general public and include those from the Noah land-surface model (LSM) version 3.3 (Noah-3.3) and the Catchment LSM version Fortuna-2.5 (CLSM-F2.5). Standard LSM output variables including soil moistures temperatures, surface fluxes, snow cover depth, groundwater, and runoff are provided, as well as streamflow using a river routing system. The NCA-LDAS data are archived at and distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The data can be accessed via HTTP, OPeNDAP, Mirador search and download, and NASA Earth data Search. To further facilitate access and use, the NCA-LDAS data are integrated into the NASA Giovanni, for quick visualization and analysis, and into the Data Rods system, for retrieval of time series of long time periods. The temporal and spatial resolutions of the NCA-LDAS data are, respectively, daily-averages and 0.125x0.125 degree, covering North America (25N 53N; 125W 67W) and the period January 1979 to December 2015. The data files are in self-describing, machine-independent, CF-compliant netCDF-4 format.

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion

Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.

Nationwide high-resolution mapping of hazards in the Philippines (Plinius Medal Lecture)

NASA Astrophysics Data System (ADS)

Lagmay, Alfredo Mahar Francisco A.

2015-04-01

The Philippines being a locus of typhoons, tsunamis, earthquakes, and volcanic eruptions, is a hotbed of disasters. Situated in a region where severe weather and geophysical unrest is common, the Philippines will inevitably suffer from calamities similar to those experienced recently. With continued development and population growth in hazard prone areas, it is expected that damage to infrastructure and human losses would persist and even rise unless appropriate measures are immediately implemented by government. Recently, the Philippines put in place a responsive program called the Nationwide Operational Assessment of Hazards (NOAH) for disaster prevention and mitigation. The efforts of Project NOAH are an offshoot of lessons learned from previous disasters that have inflicted massive loss of lives and costly damage to property. Several components of the NOAH program focus on mapping of landslide, riverine flood and storm surge inundation hazards. By simulating hazards phenomena over IFSAR- and LiDAR-derived digital terrain models (DTMs) using high-performance computers, multi-hazards maps of 1:10,000 scale, have been produced and disseminated to local government units through a variety of platforms. These detailed village-level (barangay-level) maps are useful to identify safe evacuation sites, planning emergency access routes and prepositioning of search and rescue and relief supplies during times of crises. They are also essential for long-term development planning of communities. In the past two years, NOAH was instrumental in providing timely, site-specific, and understandable hazards information to the public, considered as best practice in disaster risk reduction management (DRR). The use of advanced science and technology in the country's disaster prevention efforts is imperative to successfully mitigate the adverse impacts of natural hazards and should be a continuous quest - to find the best products, put forth in the forefront of battle against disasters.

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

LIS-HYMAP coupled Hydrological Modeling in the Nile River Basin and the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Jung, H. C.; Getirana, A.; Policelli, F. S.

2015-12-01

Water scarcity and resources in Africa have been exacerbated by periodic droughts and floods. However, few studies show the quantitative analysis of water balance or basin-scale hydrological modeling in Northeast Africa. The NASA Land Information System (LIS) is implemented to simulate land surface processes in the Nile River Basin and the Greater Horn of Africa. In this context, the Noah land surface model (LSM) and the Hydrological Modeling and Analysis Platform (HYMAP) are used to reproduce the water budget and surface water (rivers and floodplains) dynamics in that region. The Global Data Assimilation System (GDAS) meteorological dataset is used to force the system . Due to the unavailability of recent ground-based observations, satellite data are considered to evaluate first model outputs. Water levels at 10 Envisat virtual stations and water discharges at a gauging station are used to provide model performance coefficients (e.g. Nash-Sutcliffe, delay index, relative error). We also compare the spatial and temporal variations of flooded areas from the model with the Global Inundation Extent from Multi-Satellites (GIEMS) and the Alaska Satellite Facility (ASF)'s MEaSUREs Wetland data. Finally, we estimate surface water storage variations using a hypsographic curve approach with Shuttle Radar Topography Mission (SRTM) topographic data and evaluate the model-derived water storage changes in both river and floodplain. This study demonstrates the feasibility of using LIS-HYMAP coupled modeling to support seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

2011-12-01

The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the ability to detect a drought signal in modeled soil moisture and actual evapotranspiration was sensitive to parameters like minimum stomatal resistance, green vegetation fraction, and minimum threshold for transpiration stress. In addition to improving our understanding and representation of the land surface physics in agropastoral drought, this study moves us closer to confidently validating LSM estimates with remotely sensed data (e.g. MODIS NDVI), essential in regions that lack ground based measurements. Ultimately, these improved information products serve to better inform decision makers about seasonal food production and anticipate the need for relief, as well as guide climate change adaptation strategies, potentially saving millions of lives.

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

NASA Astrophysics Data System (ADS)

Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

2017-04-01

The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already operational SNPP VIIRS Green Vegetation Fraction (GVF) global gridded 4km resolution. The ultimate goal is a global consistent set of global gridded land products at 1-km resolution to enable consistent use of the products in the full suite of global and regional NCEP land models. The new JPSS vegetation products system is scheduled to transition to operations in the fall of 2017.

Benoit Mandelbrot in finance

NASA Astrophysics Data System (ADS)

Walter, Christian

2015-03-01

The following sections are included: * Introduction * The Noah and Joseph effects and the non-Gaussian and non-Brownian issues of the financial theory * The first model of Mandelbrot (1962): α-stable motion with paretian tails * The second model of Mandelbrot (1965): fractional brownian motion with aperiodic cycles * The third model of Mandelbrot (1967): time changed Brownian motion with stochastic clock * Appendix: a tale of fat tails * Bibliography

Medical Surveillance Technology - Clinical Looking Glass

DTIC Science & Technology

2012-10-01

0016 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Ms Susan Mia McCroskey, Mr. Noah Geberer , Dr. Eran Bellin 5e. TASK NUMBER...Chowdhury, Soma 0-40% Edwards, Richie 25-30% Geberer , Noah 60-70% Golden, Joe 15-30% Lee, William 0-15% McCroskey, Mia 29-50% Muresan, Mircea 0

The Impossible Voyage of Noah's Ark.

ERIC Educational Resources Information Center

Moore, Robert A.

1983-01-01

A direct and definitive response to the creationist Noah's ark arguments is presented in this publication. Although the Bible is used as a constant reference point, the author does not engage in biblical criticism. The critique is rather directed at the leading creationist books and experimental studies that seek to scientifically prove that the…

Irrigated plantations and their effect on energy fluxes in a semi-arid region of Israel - a validated 3-D model simulation

NASA Astrophysics Data System (ADS)

Branch, O.; Warrach-Sagi, K.; Wulfmeyer, V.; Cohen, S.

2013-11-01

A large irrigated biomass plantation was simulated in an arid region of Israel within the WRF-NOAH coupled atmospheric/land surface model in order to assess land surface atmosphere feedbacks. Simulations were carried out for the 2012 summer season (JJA). The irrigated plantations were simulated by prescribing tailored land surface and soil/plant parameters, and by implementing a newly devised, controllable sub-surface irrigation scheme within NOAH. Two model cases studies were considered and compared - Impact and Control. Impact simulates a hypothetical 10 km × 10 km irrigated plantation. Control represents a baseline and uses the existing land surface data, where the predominant land surface type in the area is bare desert soil. Central to the study is model validation against observations collected for the study over the same period. Surface meteorological and soil observations were made at a desert site and from a 400 ha Simmondsia chinensis (Jojoba) plantation. Control was validated with data from the desert, and Impact from the Jojoba. Finally, estimations were made of the energy balance, applying two Penman-Monteith based methods along with observed meteorological data. These estimations were compared with simulated energy fluxes. Control simulates the daytime desert surface 2 m air temperatures (T2) with less than 0.2 °C deviation and the vapour pressure deficit (VPD) to within 0.25 hPa. Desert wind speed (U) is simulated to within 0.5 m s-1 and the net surface radiation (Rn) to 25 W m-2. Soil heat flux (G) is not so accurately simulated by Control (up to 30 W m-2 deviation) and 5 cm soil temperatures (ST5) are simulated to within 1.5 °C. Impact simulates daytime T2 over irrigated vegetation to within 1-1.5 °C, the VPD to 0.5 hPa, Rn to 50 W m-2 and ST5 to within 2 °C. Simulated Impact G deviates up to 40 W m-2, highlighting a need for re-parameterisation or better soil classification, but the overall contribution to the energy balance is small (5-6%). During the night, significant T2 and ST5 cold biases of 2-4 °C are present. Diurnal latent heat values from WRF Impact correspond closely with Penman-Monteith estimation curves, and latent heat magnitudes of 160 W m-2 over the plantation are usual. Simulated plantation sensible heat fluxes are high (450 W m-2) - around 100-110 W m-2 higher than over the surrounding desert. The high relative HFX over the vegetation, driven by high Rn and high surface resistances, indicate that low Bowen ratios should not necessarily be assumed when irrigated plantations are implemented in, and optimized for arid regions. Furthermore, the high plantation T2 magnitudes highlight the importance of considering diurnal dynamics, which drive the evolution of boundary layers, rather than only on daily mean statistics which often indicate an irrigation cooling effect.

Impact of land cover data on the simulation of urban heat island for Berlin using WRF coupled with bulk approach of Noah-LSM

NASA Astrophysics Data System (ADS)

Li, Huidong; Wolter, Michael; Wang, Xun; Sodoudi, Sahar

2017-09-01

Urban-rural difference of land cover is the key determinant of urban heat island (UHI). In order to evaluate the impact of land cover data on the simulation of UHI, a comparative study between up-to-date CORINE land cover (CLC) and Urban Atlas (UA) with fine resolution (100 and 10 m) and old US Geological Survey (USGS) data with coarse resolution (30 s) was conducted using the Weather Research and Forecasting model (WRF) coupled with bulk approach of Noah-LSM for Berlin. The comparison between old data and new data partly reveals the effect of urbanization on UHI and the historical evolution of UHI, while the comparison between different resolution data reveals the impact of resolution of land cover on the simulation of UHI. Given the high heterogeneity of urban surface and the fine-resolution land cover data, the mosaic approach was implemented in this study to calculate the sub-grid variability in land cover compositions. Results showed that the simulations using UA and CLC data perform better than that using USGS data for both air and land surface temperatures. USGS-based simulation underestimates the temperature, especially in rural areas. The longitudinal variations of both temperature and land surface temperature show good agreement with urban fraction for all the three simulations. To better study the comprehensive characteristic of UHI over Berlin, the UHI curves (UHIC) are developed for all the three simulations based on the relationship between temperature and urban fraction. CLC- and UA-based simulations show smoother UHICs than USGS-based simulation. The simulation with old USGS data obviously underestimates the extent of UHI, while the up-to-date CLC and UA data better reflect the real urbanization and simulate the spatial distribution of UHI more accurately. However, the intensity of UHI simulated by CLC and UA data is not higher than that simulated by USGS data. The simulated air temperature is not dominated by the land cover as much as the land surface temperature, as air temperature is also affected by air advection.

An approximation algorithm for the Noah's Ark problem with random feature loss.

PubMed

Hickey, Glenn; Blanchette, Mathieu; Carmi, Paz; Maheshwari, Anil; Zeh, Norbert

2011-01-01

The phylogenetic diversity (PD) of a set of species is a measure of their evolutionary distinctness based on a phylogenetic tree. PD is increasingly being adopted as an index of biodiversity in ecological conservation projects. The Noah's Ark Problem (NAP) is an NP-Hard optimization problem that abstracts a fundamental conservation challenge in asking to maximize the expected PD of a set of taxa given a fixed budget, where each taxon is associated with a cost of conservation and a probability of extinction. Only simplified instances of the problem, where one or more parameters are fixed as constants, have as of yet been addressed in the literature. Furthermore, it has been argued that PD is not an appropriate metric for models that allow information to be lost along paths in the tree. We therefore generalize the NAP to incorporate a proposed model of feature loss according to an exponential distribution and term this problem NAP with Loss (NAPL). In this paper, we present a pseudopolynomial time approximation scheme for NAPL.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2015-12-01

Forest carbon processes are affected by soil moisture, soil temperature and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore they can neither resolve topographically driven hill-slope soil moisture patterns, nor simulate the nonlinear effects of soil moisture on carbon processes. A spatially-distributed biogeochemistry model, Flux-PIHM-BGC, has been developed by coupling the Biome-BGC (BBGC) model with a coupled physically-based land surface hydrologic model, Flux-PIHM. Flux-PIHM incorporates a land-surface scheme (adapted from the Noah land surface model) into the Penn State Integrated Hydrologic Model (PIHM). Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. Flux-PIHM-BGC model was tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations at the SSHCZO, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, aboveground carbon stock, and soil carbon efflux, provided an ideal test bed for the coupled model. Model results show that when uniform solar radiation is used, vegetation carbon and soil carbon are positively correlated with soil moisture in space, which agrees with the observations within the watershed. When topographically-driven solar radiation is used, however, the wetter valley floor becomes radiation limited, and produces less vegetation and soil carbon than the drier hillslope due to the assumption that canopy height is uniform in the watershed. This contradicts with the observations, and suggests that a tree height model with dynamic allocation model are needed to reproduce the spatial variation of carbon processes within a watershed.

Observed and Simulated Urban Heat Island and Urban Cool Island in Las Vegas

NASA Astrophysics Data System (ADS)

Sauceda, Daniel O.

This research investigates the urban climate of Las Vegas and establishes long-term trends relative to the regional climate in an attempt to identify climate disturbances strictly related to urban growth. An experimental surface station network (DRI-UHI) of low-cost surface temperature (T2m) and relative humidity (RH) sensors were designed to cover under-sampled low-intensity residential urban areas, as well as complement the in-city and surrounding rural areas. In addition to the analysis of the surface station data, high-resolution gridded data products (GDPs) from Daymet (1km) and PRISM (800 m) and results from numerical simulations were used to further characterize the Las Vegas climate trends. The Weather Research and Forecasting (WRF) model was coupled with three different models: the Noah Land Surface Model (LSM) and a single- and multi-layer urban canopy model (UCM) to assess the urban related climate disturbances; as well as the model sensitivity and ability to characterize diurnal variability and rural/urban thermal contrasts. The simulations consisted of 1 km grid size for five, one month-long hindcast simulations during November of 2012: (i) using the Noah LSM without UCM treatment, (ii) same as (i) with a single-layer UCM (UCM1), (iii) same as (i) with a multi-layer UCM (UCM2), (iv) removing the City of Las Vegas (NC) and replacing it with predominant land cover (shrub), and (v) same as (ii) with increasing the albedo of rooftops from 0.20 to 0.65 as a potential adaptation scenario known as "white roofing". T2m long-term trends showed a regional warming of minimum temperatures (Tmin) and negligible trends in maximum temperatures (Tmax ). By isolating the regional temperature trends, an observed urban heat island (UHI) of ~1.63°C was identified as well as a daytime urban cool island (UCI) of ~0.15°C. GDPs agree with temperature trends but tend to underpredict UHI intensity by ~1.05°C. The WRF-UCM showed strong correlations with observed T2m (0.85 < rho < 0.95) and vapor pressure (ea ; 0.83 < rho < 0.88), and moderate-to-strong correlations for RH (0.64 < rho < 0.81) at the 95% confidence level. UCM1 shows the best skill and adequately simulates most of the UHI and UCI observed characteristics. Differences of LSM, UCM1, and UCM2 minus NC show simulated effects of warmer in-city Tmin for LSM and UCM2, and cooler in-city Tmax for UCM1 and UCM2. Finally, the white roofing scenario for Las Vegas was not found to significantly impact the UHI effect but has the potential to reduce daytime temperature by 1°-2°C.

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther, Alex; Gu, Dasa; Shrivastava, Manish; Liu, Ying; Walters, Stacy; Pfister, Gabriele; Jin, Jiming; Shilling, John E.; Warneke, Carsten

2016-05-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Talking and Writing about Noah Variants.

ERIC Educational Resources Information Center

Stewig, John Warren

1997-01-01

Examines student responses to four versions of the Noah's Ark tale. Finds that the second- and fourth-grade children were interested in talking about the visuals in picture books. Notes a wide range in the amount of writing children did in response to the art, and that the written products were far less skilled and spirited than the discussion.…

Response to Noah Sobe's "Rethinking "Cosmopolitanism" as an Analytic for the Comparative Study of Globalization and Education"

ERIC Educational Resources Information Center

Wisler, Andria

2010-01-01

As a springboard into her response inspired by Noah Sobe's article, this author offers two possibilities for what cosmopolitanisms can tell about comparative and international education research. First, from her perspective, rooted in justice and peace studies, she is intrigued by several authors' assessments of cosmopolitanism as a cognitive or…

Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

High resolution land surface response of inland moving Indian monsoon depressions over Bay of Bengal

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.

2016-05-01

During Indian summer monsoon (ISM) season, nearly about half of the monsoonal rainfall is brought inland by the low pressure systems called as Monsoon Depressions (MDs). These systems bear large amount of rainfall and frequently give copious amount of rainfall over land regions, therefore accurate forecast of these synoptic scale systems at short time scale can help in disaster management, flood relief, food safety. The goal of this study is to investigate, whether an accurate moisture-rainfall feedback from land surface can improve the prediction of inland moving MDs. High Resolution Land Data Assimilation System (HRLDAS) is used to generate improved land state .i.e. soil moisture and soil temperature profiles by means of NOAH-MP land-surface model. Validation of the model simulated basic atmospheric parameters at surface layer and troposphere reveals that the incursion of high resolution land state yields least Root Mean Squared Error (RMSE) with a higher correlation coefficient and facilitates accurate depiction of MDs. Rainfall verification shows that HRLDAS simulations are spatially and quantitatively in more agreement with the observations and the improved surface characteristics could result in the realistic reproduction of the storm spatial structure, movement as well as intensity. These results signify the necessity of investigating more into the land surface-rainfall feedbacks through modifications in moisture flux convergence within the storm.

Cross-compartment evaluation of a fully-coupled hydrometeorological modeling system using comprehensive observation data

NASA Astrophysics Data System (ADS)

Fersch, Benjamin; Senatore, Alfonso; Kunstmann, Harald

2017-04-01

Fully-coupled hydrometeorological modeling enables investigations about the complex and often non-linear exchange mechanisms among subsurface, land, and atmosphere with respect to water and energy fluxes. The consideration of lateral redistribution of surface and subsurface water in such modeling systems is a crucial enhancement, allowing for a better representation of surface spatial patterns and providing also channel discharge predictions. However, the evaluation of fully-coupled simulations is difficult since the amount of physical detail along with feedback mechanisms leads to high degrees of freedom. Therefore, comprehensive observation data is required to obtain meaningful model configurations. We present a case study for a medium-sized river catchment in southern Germany that includes the calibration of the stand-alone and the evaluation of the fully-coupled WRF-Hydro modeling system with a horizontal resolution of 1 x 1 km2, for the period June to August 2015. ECMWF ERA-Interim reanalysis is used for model driving. Land-surface processes are represented by the Noah-MP land surface model. Land-cover is described by the EU CORINE data set. Observations for model evaluation are obtained from the TERENO Pre-Alpine observatory (http://www.imk-ifu.kit.edu/tereno.php) and are complemented by further measurements from the ScaleX campaign (http://scalex.imk-ifu.kit.edu) such as atmospheric profiles obtained from radiometer sounding and airborne systems as well as soil moisture and -temperature networks. We show how well water budgets and heat-fluxes are being reproduced by the stand-alone WRF, the stand-alone WRF-Hydro and the fully-coupled WRF-Hydro model.

Estimating Evapotranspiration with Land Data Assimilation Systems

NASA Technical Reports Server (NTRS)

Peters-Lidard, C. D.; Kumar, S. V.; Mocko, D. M.; Tian, Y.

2011-01-01

Advancements in both land surface models (LSM) and land surface data assimilation, especially over the last decade, have substantially advanced the ability of land data assimilation systems (LDAS) to estimate evapotranspiration (ET). This article provides a historical perspective on international LSM intercomparison efforts and the development of LDAS systems, both of which have improved LSM ET skill. In addition, an assessment of ET estimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 (NLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

Evaluation of an urban canopy model in a tropical city: the role of tree evapotranspiration

NASA Astrophysics Data System (ADS)

Liu, Xuan; Li, Xian-Xiang; Harshan, Suraj; Roth, Matthias; Velasco, Erik

2017-09-01

A single layer urban canopy model (SLUCM) with enhanced hydrologic processes, is evaluated in a tropical city, Singapore. The evaluation was performed using an 11 month offline simulation with the coupled Noah land surface model/SLUCM over a compact low-rise residential area. Various hydrological processes are considered, including anthropogenic latent heat release, and evaporation from impervious urban facets. Results show that the prediction of energy fluxes, in particular latent heat flux, is improved when these processes were included. However, the simulated latent heat flux is still underestimated by ∼40%. Considering Singapore’s high green cover ratio, the tree evapotranspiration process is introduced into the model, which significantly improves the simulated latent heat flux. In particular, the systematic error of the model is greatly reduced, and becomes lower than the unsystematic error in some seasons. The effect of tree evapotranspiration on the urban surface energy balance is further demonstrated during an unusual dry spell. The present study demonstrates that even at sites with relatively low (11%) tree coverage, ignoring evapotranspiration from trees may cause serious underestimation of the latent heat flux and atmospheric humidity. The improved model is also transferable to other tropical or temperate regions to study the impact of tree evapotranspiration on urban climate.

Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

NASA Technical Reports Server (NTRS)

Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

2011-01-01

Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Shukla, Shraddhanand; Arsenault, Kristi R.; Getirana, Augusto; Kumar, Sujay V.; Roningen, Jeanne; Zaitchik, Ben; McNally, Amy; Koster, Randal D.; Peters-Lidard, Christa

2017-04-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. A seamless and effective monitoring and early warning system is needed by regional/national stakeholders. Such system should support a proactive drought management approach and mitigate the socio-economic losses up to the extent possible. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of the LIS models used for drought and water availability monitoring in the region. The second part will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the monitoring and forecasting products through NASA's web-services. The water deficit forecasting system thus far incorporates NOAA's Noah land surface model (LSM), version 3.3, the Variable Infiltration Capacity (VIC) model, version 4.12, NASA GMAO's Catchment LSM, and the Noah Multi-Physics (MP) LSM (the latter two incorporate prognostic water table schemes). In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. The LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. The LIS software framework integrates these forcing datasets and drives the four LSMs and HyMAP. The Land Verification Toolkit (LVT) is used for the evaluation of the LSMs, as it provides model ensemble metrics and the ability to compare against a variety of remotely sensed measurements, like different evapotranspiration (ET) and soil moisture products, and other reanalysis datasets that are available for this region. Comparison of the models' energy and hydrological budgets will be shown for this region (and sub-basin level, e.g., Blue Nile River) and time period (1981-2015), along with evaluating ET, streamflow, groundwater storage and soil moisture, using evaluation metrics (e.g., anomaly correlation, RMSE, etc.). The system uses seasonal climate forecasts from NASA's GMAO (the Goddard Earth Observing System Model, version 5) and NCEP's Climate Forecast System, version 2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region.

U.S. Social and Educational Research during the Cold War: An Interview with Harold J. Noah

ERIC Educational Resources Information Center

Steiner-Khamsi, Gita

2006-01-01

This article presents an interview with Harold J. Noah, Gardner Cowles Professor Emeritus of Economics and Education and former dean at Teachers College, Columbia University, New York. He edited the "Comparative Education Review" from 1965 to 1971, was president of the U.S. Comparative and International Education Society in 1973, and is…

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE PAGES

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; ...

2017-01-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

NASA Astrophysics Data System (ADS)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; Berg, Larry K.; Fast, Jerome D.; Easter, Richard C.; Shrivastava, Manish; Thomas, Jennie L.

2017-10-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain-Fritsch + Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model withmore » chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.« less

Perfect Prophets, Helpful Hippos, and Happy Endings: Noah and Jonah in Children's Bible Storybooks in the United States

ERIC Educational Resources Information Center

Dalton, Russell W.

2007-01-01

This article is based on a study of hundreds of children's bible storybooks available in the United States from 1850 to the present and focuses on the way the biblical stories of Noah and Jonah have been retold for children. These children's bible storybooks lend insight into the American church's changing assumptions about the purpose of the…

Language of sport fans: sportugese revisited.

PubMed

Wann, D L; Metcalf, L A; Adcock, M L; Choi, C C; Dallas, M B; Slaton, E

1997-12-01

In 1959, Tannenbaum and Noah reported that sports writers and readers possessed a better understanding of sport terminology than nonreaders. The current investigation extended Tannenbaum and Noah's research using current sport terms. A positive relationship between understanding sport terminology, extent of team identification, strength of sport fandom, and self-proclaimed sport knowledge was hypothesized. Scores of 57 participants confirmed the predicted pattern. Discussion concerned research examining sport terminology.

A Method for a Multi-Platform Approach to Generate Gridded Surface Evaporation

NASA Astrophysics Data System (ADS)

Badger, A.; Livneh, B.; Small, E. E.; Abolafia-Rosenzweig, R.

2017-12-01

Evapotranspiration is an integral component of the surface water balance. While there are many estimates of evapotranspiration, there are fewer estimates that partition evapotranspiration into evaporation and transpiration components. This study aims to generate a CONUS-scale, observationally-based soil evaporation dataset by using the time difference of surface soil moisture by Soil Moisture Active Passive (SMAP) satellite with adjustments for transpiration and a bottom flux out of the surface layer. In concert with SMAP, the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite, North American Land Data Assimilation Systems (NLDAS) and the Hydrus-1D model are used to fully analyze the surface water balance. A biome specific estimate of the total terrestrial ET is calculated through a variation of the Penman-Monteith equation with NLDAS forcing and NLDAS Noah Model output for meteorological variables. A root density restriction and SMAP-based soil moisture restriction are applied to obtain terrestrial transpiration estimates. By forcing Hydrus-1D with NLDAS meteorology and our terrestrial transpiration estimates, an estimate of the flux between the soil surface and root zone layers (qbot) will dictate the proportion of water that is available for soil evaporation. After constraining transpiration and the bottom flux from the surface layer, we estimate soil evaporation as the residual of the surface water balance. Application of this method at Fluxnet sites shows soil evaporation estimates of approximately 0­3 mm/day and less than ET estimates. Expanding this methodology to produce a gridded product for CONUS, and eventually a global-scale product, will enable a better understanding of water balance processes and contribute a dataset to validate land-surface model's surface flux processes.

Diagnosing the influence of model structure on the simulation of water, energy and carbon fluxes on bark beetle infested forests

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Gutmann, E. D.; Brooks, P. D.; Reed, D. E.; Ewers, B. E.; Pendall, E.; Biederman, J. A.; Harpold, A. A.; Barnard, H. R.; Hu, J.

2011-12-01

Forest dynamics induced by insect infestation can have a significant, local impact on plant physiological regulation of water, energy and carbon fluxes. Rapid mortality succeeded by more gradually varying land cover changes are presently thought to initiate a cascade of changes to water, energy and carbon budgets at the forest stand scale. Initial model sensitivity results have suggested very strong changes in land-atmosphere exchanges of these variables. Specifically, model results from the Noah land surface model, a relatively simple model, have suggested that loss of transpiration function may result in a nearly 50% increase in seasonal soil moisture values and similar increases in runoff production for locations in the central Rocky Mountains. However, differing model structures, such as the representation of plant canopy architecture, snowpack dynamics, dynamic vegetation and hillslope hydrologic processes, may significantly confound the synthesis of results from different modeling systems. We assess the performance of new suite of model simulations from three different land surface models of differing model structures and complexity levels against a comprehensive set of field observations of land surface flux and state variables. The focus of the analysis is in diagnosing how model structure influences changes in energy, water and carbon budget partitioning prior to and following insect infestation. Specific emphasis in this presentation is placed on verifying variables that characterize top of canopy and within canopy energy and water fluxes. We conclude the presentation with a set of recommendations about the advantages and disadvantages of various model structures in their simulation of insect driven forest dynamics.

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Noah, Joseph and Convex Hulls

NASA Astrophysics Data System (ADS)

Watkins, N. W.; Chau, Y.; Chapman, S. C.

2010-12-01

The idea of describing animal movement by mathematical models based on diffusion and Brownian motion has a long heritage. It has thus been natural to account for those aspects of motion that depart from the Brownian by the use of models incorporating long memory & subdiffusion (“the Joseph effect”) and/or heavy tails & superdiffusion (“the Noah effect”). My own interest in this problem was originally from a geoscience perspective, and was triggered by the need to model time series in space physics where both effects coincide. Subsequently I have been involved in animal foraging studies [e.g. Edwards et al, Nature, 2007]. I will describe some recent work [Watkins et al, PRE, 2009] which studies how fixed-timestep and variable-timestep formulations of anomalous diffusion are related in the presence of heavy tails and long range memory (stable processes versus the CTRW). Quantities for which different scaling relations are predicted between the two approaches are of particular interest, to aid testability. I will also present some of work in progress on the convex hull of anomalously diffusing walkers, inspired by its possible relevance to the idea of home range in biology, and by Randon-Furling et al’s recent analytical results in the Brownian case [PRL, 2009].

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2010-10-01

The impact of urban surface parameterizations in the WRF (Weather Research and Forecasting) model on the simulation of local meteorological fields is investigated. The Noah land surface model (LSM), a modified LSM, and a single-layer urban canopy model (UCM) have been compared, focusing on urban patches. The model simulations were performed for 6 days from 12 August to 17 August during the Texas Air Quality Study 2006 field campaign. Analysis was focused on the Houston-Galveston metropolitan area. The model simulated temperature, wind, and atmospheric boundary layer (ABL) height were compared with observations from surface meteorological stations (Continuous Ambient Monitoring Stations, CAMS), wind profilers, the NOAA Twin Otter aircraft, and the NOAA Research Vessel Ronald H. Brown. The UCM simulation showed better results in the comparison of ABL height and surface temperature than the LSM simulations, whereas the original LSM overestimated both the surface temperature and ABL height significantly in urban areas. The modified LSM, which activates hydrological processes associated with urban vegetation mainly through transpiration, slightly reduced warm and high biases in surface temperature and ABL height. A comparison of surface energy balance fluxes in an urban area indicated the UCM reproduces a realistic partitioning of sensible heat and latent heat fluxes, consequently improving the simulation of urban boundary layer. However, the LSMs have a higher Bowen ratio than the observation due to significant suppression of latent heat flux. The comparison results suggest that the subgrid heterogeneity by urban vegetation and urban morphological characteristics should be taken into account along with the associated physical parameterizations for accurate simulation of urban boundary layer if the region of interest has a large fraction of vegetation within the urban patch. Model showed significant discrepancies in the specific meteorological conditions when nocturnal low-level jets exist and a thermal internal boundary layer over water forms.

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2011-03-01

The performance of different urban surface parameterizations in the WRF (Weather Research and Forecasting) in simulating urban boundary layer (UBL) was investigated using extensive measurements during the Texas Air Quality Study 2006 field campaign. The extensive field measurements collected on surface (meteorological, wind profiler, energy balance flux) sites, a research aircraft, and a research vessel characterized 3-dimensional atmospheric boundary layer structures over the Houston-Galveston Bay area, providing a unique opportunity for the evaluation of the physical parameterizations. The model simulations were performed over the Houston metropolitan area for a summertime period (12-17 August) using a bulk urban parameterization in the Noah land surface model (original LSM), a modified LSM, and a single-layer urban canopy model (UCM). The UCM simulation compared quite well with the observations over the Houston urban areas, reducing the systematic model biases in the original LSM simulation by 1-2 °C in near-surface air temperature and by 200-400 m in UBL height, on average. A more realistic turbulent (sensible and latent heat) energy partitioning contributed to the improvements in the UCM simulation. The original LSM significantly overestimated the sensible heat flux (~200 W m-2) over the urban areas, resulting in warmer and higher UBL. The modified LSM slightly reduced warm and high biases in near-surface air temperature (0.5-1 °C) and UBL height (~100 m) as a result of the effects of urban vegetation. The relatively strong thermal contrast between the Houston area and the water bodies (Galveston Bay and the Gulf of Mexico) in the LSM simulations enhanced the sea/bay breezes, but the model performance in predicting local wind fields was similar among the simulations in terms of statistical evaluations. These results suggest that a proper surface representation (e.g. urban vegetation, surface morphology) and explicit parameterizations of urban physical processes are required for accurate urban atmospheric numerical modeling.

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

Influence of the long-range transport of dust over central Himalayan region - study using MERRA-2 and GLDAS Ver.2.1

NASA Astrophysics Data System (ADS)

Kumar, A.; Singh, N.; A.

2017-12-01

To elucidate upon the effect of dust loading on the central Himalayan glaciers and snow cover, a study is carried out over the geographical boundary between 28-34° N and 78-98° E, for the period 2011-2015. Only spring and summer seasons are investigated, as the long range transport over the region are usually more prominent during these seasons. To ascertain the dust sources, data obtained from the level-2 of Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations (CALIPSO) ver. 4.10, Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectory model, Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) ver. 5.12.4 are utilized. The snow depth and snow fall data are taken from MERRA-2, while, for the surface Albedo, data from Global land data assimilation system (GLDAS) ver. 2.1 Noah land surface model L4 is used. ERA-Interim wind products are also used to understand the prevailing wind pattern over the site during the period of study. To show the impact of aerosols on glaciated surface and the snow fall, a regression analysis is performed between these parameters and the dust column mass density for the period of 1980-2016 using MERRA-2 reanalysis data.

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Assessment of Irrigation Physics in a Land Surface Modeling Framework Using Non-Traditional and Human-Practice Datasets

NASA Technical Reports Server (NTRS)

Lawston, Patricia M.; Santanello, Joseph A.; Rodell, Matthew; Franz, Trenton E.

2017-01-01

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the10 planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASAs Land15 Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results20 show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation foraccurate simulation of water and energy states and fluxes over cropland.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Applying Geospatial Techniques to Investigate Boundary Layer Land-Atmosphere Interactions Involved in Tornadogensis

NASA Astrophysics Data System (ADS)

Weigel, A. M.; Griffin, R.; Knupp, K. R.; Molthan, A.; Coleman, T.

2017-12-01

Northern Alabama is among the most tornado-prone regions in the United States. This region has a higher degree of spatial variability in both terrain and land cover than the more frequently studied North American Great Plains region due to its proximity to the southern Appalachian Mountains and Cumberland Plateau. More research is needed to understand North Alabama's high tornado frequency and how land surface heterogeneity influences tornadogenesis in the boundary layer. Several modeling and simulation studies stretching back to the 1970's have found that variations in the land surface induce tornadic-like flow near the surface, illustrating a need for further investigation. This presentation introduces research investigating the hypothesis that horizontal gradients in land surface roughness, normal to the direction of flow in the boundary layer, induce vertically oriented vorticity at the surface that can potentially aid in tornadogenesis. A novel approach was implemented to test this hypothesis using a GIS-based quadrant pattern analysis method. This method was developed to quantify spatial relationships and patterns between horizontal variations in land surface roughness and locations of tornadogenesis. Land surface roughness was modeled using the Noah land surface model parameterization scheme which, was applied to MODIS 500 m and Landsat 30 m data in order to compare the relationship between tornadogenesis locations and roughness gradients at different spatial scales. This analysis found a statistical relationship between areas of higher roughness located normal to flow surrounding tornadogenesis locations that supports the tested hypothesis. In this presentation, the innovative use of satellite remote sensing data and GIS technologies to address interactions between the land and atmosphere will be highlighted.

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

NASA Technical Reports Server (NTRS)

Zaitchik, Benjamin F.; Rodell, Matthew

2008-01-01

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

Assessing the Effects of Irrigation on Land Surface Processes Utilizing CLM.PF in Los Angeles, California

NASA Astrophysics Data System (ADS)

Reyes, B.; Vahmani, P.; Hogue, T. S.; Maxwell, R. M.

2013-05-01

Irrigation can significantly alter land surface properties including increases in evapotranspiration (ET) and latent heat flux and a decrease in land surface temperatures that have a wide range of effects on the hydrologic cycle. However, most irrigation in land surface modeling studies has generally been limited to large-scale cropland applications while ignoring the, relatively, much smaller use of irrigation in urban areas. Although this assumption may be valid in global studies, as we seek to apply models at higher resolutions and at more local scales, irrigation in urban areas can become a key factor in land-atmosphere interactions. Landscape irrigation can account for large portions of residential urban water use, especially in semi-arid environments (e.g. ~50% in Los Angeles, CA). Previous modeling efforts in urbanized semi-arid regions have shown that disregarding irrigation leads to inaccurate representation of the energy budget. The current research models a 49.5-km2 (19.11-mi2) domain near downtown Los Angeles in the Ballona Creek watershed at a high spatial and temporal resolution using a coupled hydrologic (ParFlow) and land surface model (CLM). Our goals are to (1) provide a sensitivity analysis for urban irrigation parameters including sensitivity to total volume and timing of irrigation, (2) assess the effects of irrigation on varying land cover types on the energy budget, and (3) evaluate if residential water use data is useful in providing estimates for irrigation in land surface modeling. Observed values of land surface parameters from remote sensing products (Land Surface Temperature and ET), water use data from the Los Angeles Department of Water and Power (LADWP), and modeling results from an irrigated version of the NOAH-Urban Canopy Model are being used for comparison and evaluation. Our analysis provides critical information on the degree to which urban irrigation should be represented in high-resolution, semi-arid urban land surface modeling of the region. This research also yields robust upper-boundary conditions for further analysis and modeling in Los Angeles.

3D Surface Temperature Measurement of Plant Canopies Using Photogrammetry Techniques From A UAV.

NASA Astrophysics Data System (ADS)

Irvine, M.; Lagouarde, J. P.

2017-12-01

Surface temperature of plant canopies and within canopies results from the coupling of radiative and energy exchanges processes which govern the fluxes at the interface soil-plant-atmosphere. As a key parameter, surface temperature permits the estimation of canopy exchanges using processes based modeling methods. However detailed 3D surface temperature measurements or even profile surface temperature measurements are rarely made as they have inherent difficulties. Such measurements would greatly improve multi-level canopy models such as NOAH (Chen and Dudhia 2001) or MuSICA (Ogée and Brunet 2002, Ogée et al 2003) where key surface temperature estimations, at present, are not tested. Additionally, at larger scales, canopy structure greatly influences satellite based surface temperature measurements as the structure impacts the observations which are intrinsically made at varying satellite viewing angles and solar heights. In order to account for these differences, again accurate modeling is required such as through the above mentioned multi-layer models or with several source type models such as SCOPE (Van der Tol 2009) in order to standardize observations. As before, in order to validate these models, detailed field observations are required. With the need for detailed surface temperature observations in mind we have planned a series of experiments over non-dense plant canopies to investigate the use of photogrammetry techniques. Photogrammetry is normally used for visible wavelengths to produce 3D images using cloud point reconstruction of aerial images (for example Dandois and Ellis, 2010, 2013 over a forest). From these cloud point models it should be possible to establish 3D plant surface temperature images when using thermal infrared array sensors. In order to do this our experiments are based on the use of a thermal Infrared camera embarked on a UAV. We adapt standard photogrammetry to account for limits imposed by thermal imaginary, especially the low image resolution compared with standard RGB sensors. At the session B081, we intend to present first results of our thermal photogrammetric experiments with 3D surface temperature plots in order to discuss and adapt our methods to the modelling community's needs.

NCA-LDAS: A Terrestrial Water Analysis System Enabling Sustained Assessment and Dissemination of National Climate Indicators

NASA Astrophysics Data System (ADS)

Jasinski, M. F.; Kumar, S.; Peters-Lidard, C. D.; Arsenault, K. R.; Beaudoing, H. K.; Bolten, J. D.; Borak, J.; Kempler, S.; Li, B.; Mocko, D. M.; Rodell, M.; Rui, H.; Silberstein, D. S.; Teng, W. L.; Vollmer, B.

2016-12-01

The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is an integrated terrestrial water analysis system created as an end-to-end enabling tool for sustained assessment and dissemination of terrestrial hydrologic indicators in support of the NCA. The primary features are i) gridded, daily time series of over forty hydrologic variables including terrestrial water and energy balance stores, states and fluxes over the continental U.S. derived from land surface modeling with multivariate satellite data record assimilation (1979-2015), ii) estimated trends of the principal water balance components over a wide range of scales and locations, and iii) public dissemination of all NCA-LDAS model forcings, and input and output data products through dedicated NCA-LDAS and NASA GES-DISC websites. NCA-LDAS supports sustained assessment of our national terrestrial hydrologic climate for improved scientific understanding, and the adaptation and management of water resources and related energy sectors. This presentation provides an overview of the NCA-LDAS system together with an evaluation of the initial release of NCA-LDAS data products and trends using two land surface models; Noah Ver. 3.3 and Catchment Ver. Fortuna 2.5, and a listing of several available pathways for public access and visualization of NCA-LDAS background information and data products.

The Effects of Implementing TopModel Concepts in the Noah Model

NASA Technical Reports Server (NTRS)

Peters-Lidard, C. D.; Houser, Paul R. (Technical Monitor)

2002-01-01

Topographic effects on runoff generation have been documented observationally (e.g., Dunne and Black, 1970) and are the subject of the physically based rainfall-runoff model TOPMODEL (Beven and Kirkby, 1979; Beven, 1986a;b) and its extensions, which incorporate variable soil transmissivity effects (Sivapalan et al, 1987, Wood et al., 1988; 1990). These effects have been shown to exert significant control over the spatial distribution of runoff, soil moisture and evapotranspiration, and by extension, the latent and sensible heat fluxes

Evaluation of the North American Land Data Assimilation System over the Southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, A.; Luo, L.; Wood, E. F.; Wen, F.; Mitchell, K. E.; Houser, P. R.; Schaake, J. C.; Nldas Team

2003-04-01

To conduct land data assimilation, validated land surface models are needed. The first step in the North American Land Data Assimilation System (NLDAS) is to evaluate four such state-of-the-art models. These models (VIC, Noah, Mosaic, and Sacramento) have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation (on a 1/8 degree North American grid) to calculate land hydrology. First we show that the forcing data set agrees very well with local observations and that simulations forced with local observations differ little from those forced with the NLDAS forcing data set. Then we evaluated the simulations using in situ observations over the Southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Rapid prototyping of soil moisture estimates using the NASA Land Information System

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mostovoy, G.; Li, B.; Peters-Lidard, C.; Houser, P.; Moorhead, R.; Kumar, S.

2007-12-01

The Land Information System (LIS), developed at the NASA Goddard Space Flight Center, is a functional Land Data Assimilation System (LDAS) that incorporates a suite of land models in an interoperable computational framework. LIS has been integrated into a computational Rapid Prototyping Capabilities (RPC) infrastructure. LIS consists of a core, a number of community land models, data servers, and visualization systems - integrated in a high-performance computing environment. The land surface models (LSM) in LIS incorporate surface and atmospheric parameters of temperature, snow/water, vegetation, albedo, soil conditions, topography, and radiation. Many of these parameters are available from in-situ observations, numerical model analysis, and from NASA, NOAA, and other remote sensing satellite platforms at various spatial and temporal resolutions. The computational resources, available to LIS via the RPC infrastructure, support e- Science experiments involving the global modeling of land-atmosphere studies at 1km spatial resolutions as well as regional studies at finer resolutions. The Noah Land Surface Model, available with-in the LIS is being used to rapidly prototype soil moisture estimates in order to evaluate the viability of other science applications for decision making purposes. For example, LIS has been used to further extend the utility of the USDA Soil Climate Analysis Network of in-situ soil moisture observations. In addition, LIS also supports data assimilation capabilities that are used to assimilate remotely sensed soil moisture retrievals from the AMSR-E instrument onboard the Aqua satellite. The rapid prototyping of soil moisture estimates using LIS and their applications will be illustrated during the presentation.

mRM - multiscale Routing Model for Land Surface and Hydrologic Models

NASA Astrophysics Data System (ADS)

Cuntz, M.; Thober, S.; Mai, J.; Samaniego, L. E.; Gochis, D. J.; Kumar, R.

2015-12-01

Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID), and hydrologic models (e.g., the mesoscale Hydrologic Model). Most implementations suffer from a high computational demand because the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This is because the model parameters are scale-dependent and cannot be used at other resolutions without re-estimation. Here, we present the multiscale Routing Model (mRM) that allows for a flexible choice of the routing resolution. mRM exploits the Multiscale Parameter Regionalization (MPR) included in the open-source mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) that relates model parameters to physiographic properties and allows to estimate scale-independent model parameters. mRM is currently coupled to mHM and is presented here as stand-alone Free and Open Source Software (FOSS). The mRM source code is highly modular and provides a subroutine for internal re-use in any land surface scheme. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulation results using mRM are compared with those available in WRF-HYDRO for the Red River during the period 1990-2000. mRM allows to increase the routing resolution from 100m to more than 10km without deteriorating the model performance. Therefore, it speeds up model calculation by reducing the contribution of routing to total runtime from over 80% to less than 5% in the case of WRF-HYDRO. mRM thus makes discharge data available to land surface modeling with only little extra calculations.

Proceedings of Joint RL/AFOSR Workshop on Intelligent Information Systems Held at Griffiss AFB, New York on October 22-23, 1991

DTIC Science & Technology

1992-04-01

AND SCHEDULING" TIM FINN, UNIVERSITY OF MARYLAND, BALTIMORE COUNTY E. " EXTRACTING RULES FROM SOFTWARE FOR KNOWLEDGE-BASES" NOAH S. PRYWES, UNIVERSITY...Databases for Planning and Scheduling" Tim Finin, Unisys Corporation 8:30 - 9:00 " Extracting Rules from Software for Knowledge Baseso Noah Prywes, U. of...Space Requirements are Tractable E.G.: FEM, Multiplication Routines, Sorting Programs Lebmwmy fo Al Roseew d. The Ohio Male Unlversity A-2 Type 2

NASA GLDAS Evapotranspiration Data and Climatology

NASA Technical Reports Server (NTRS)

Rui, Hualan; Beaudoing, Hiroko Kato; Teng, William L.; Vollmer, Bruce; Rodell, Matthew

2012-01-01

Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.

Fractal and multifractal models for extreme bursts in space plasmas.

NASA Astrophysics Data System (ADS)

Watkins, Nicholas; Chapman, Sandra; Credgington, Dan; Rosenberg, Sam; Sanchez, Raul

2010-05-01

Space plasmas may be said to show at least two types of "universality". One type arises from the fact that plasma physics underpins all astrophysical systems, while another arises from the generic properties of coupled nonlinear physical systems, a branch of the emerging science of complexity. Much work in complexity science is contributing to the physical understanding of the ways by which complex interactions in such systems cause driven or random perturbations to be nonlinearly amplified in amplitude and/or spread out over a wide range of frequencies. These mechanisms lead to non-Gaussian fluctuations and long-ranged temporal memory (referred to by Mandelbrot as the "Noah" and "Joseph" effects, respectively). This poster discusses a standard toy model (linear fractional stable motion, LFSM) which combines the Noah and Joseph effects in a controllable way. I will describe how LFSM is being used to explore the interplay of the above two effects in the distribution of bursts above thresholds, with applications to extreme events in space time series. I will describe ongoing work to improve the accuracy of maximum likelihood-based estimation of burst size and waiting time distributions for LFSM first reported in Watkins et al [Space Science Review, 2005; PRE, 2009]. The relevance of turbulent cascades to space plasmas necessitates comparison between this model and multifractal models, and early results will be described [Watkins et al, PRL comment, 2009].

Moving Beyond Streamflow Observations: Lessons From A Multi-Objective Calibration Experiment in the Mississippi Basin

NASA Astrophysics Data System (ADS)

Koppa, A.; Gebremichael, M.; Yeh, W. W. G.

2017-12-01

Calibrating hydrologic models in large catchments using a sparse network of streamflow gauges adversely affects the spatial and temporal accuracy of other water balance components which are important for climate-change, land-use and drought studies. This study combines remote sensing data and the concept of Pareto-Optimality to address the following questions: 1) What is the impact of streamflow (SF) calibration on the spatio-temporal accuracy of Evapotranspiration (ET), near-surface Soil Moisture (SM) and Total Water Storage (TWS)? 2) What is the best combination of fluxes that can be used to calibrate complex hydrological models such that both the accuracy of streamflow and the spatio-temporal accuracy of ET, SM and TWS is preserved? The study area is the Mississippi Basin in the United States (encompassing HUC-2 regions 5,6,7,9,10 and 11). 2003 and 2004, two climatologically average years are chosen for calibration and validation of the Noah-MP hydrologic model. Remotely sensed ET data is sourced from GLEAM, SM from ESA-CCI and TWS from GRACE. Single objective calibration is carried out using DDS Algorithm. For Multi objective calibration PA-DDS is used. First, the Noah-MP model is calibrated using a single objective function (Minimize Mean Square Error) for the outflow from the 6 HUC-2 sub-basins for 2003. Spatial correlograms are used to compare the spatial structure of ET, SM and TWS between the model and the remote sensing data. Spatial maps of RMSE and Mean Error are used to quantify the impact of calibrating streamflow on the accuracy of ET, SM and TWS estimates. Next, a multi-objective calibration experiment is setup to determine the pareto optimal parameter sets (pareto front) for the following cases - 1) SF and ET, 2) SF and SM, 3) SF and TWS, 4) SF, ET and SM, 5) SF, ET and TWS, 6) SF, SM and TWS, 7) SF, ET, SM and TWS. The best combination of fluxes that provides the optimal trade-off between accurate streamflow and preserving the spatio-temporal structure of ET, SM and TWS is then determined by validating the model outputs for the pareto-optimal parameter sets. Results from single-objective calibration experiment with streamflow shows that it does indeed negatively impact the accuracy of ET, SM and TWS estimates.

Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

2014-12-01

A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis products, soil databases and land cover databases (e.g., NLDAS-2, SSURGO, NLCD) can provide high resolution forcing and input data. Therefore the Flux-PIHM data assimilation system could be readily expanded to other watersheds to provide regional scale land surface and hydrologic reanalysis with high spatial temporal resolution.

Assessment of an improved hydrological loading model from space geodesy: case study in South America

NASA Astrophysics Data System (ADS)

Nicolas, Joëlle; Boy, Jean-Paul; Durand, Frédéric; Mémin, Anthony

2017-04-01

Loading effects are crustal deformations induced by ocean, atmosphere and continental water mass redistributions. In this study we focus on hydrological loading effect monitored by space geodesy and in particular by GNSS and GRACE. Classically, hydrological loading models take into account snow and soil-moisture but don't consider surface waters (rivers, lakes…). As a result, huge discrepancies between GPS observations and those models arise around large rivers such as the Amazon where nearly half of the vertical signal cannot be explained by the combination of atmospheric, oceanic and hydrological loading models. To better resolve the hydrological signal, we improve the continental water storage models computed from soil-moisture and snow GLDAS/Noah or MERRA data sets by including surface water runoff. We investigate how continental water storage model improvements are supported by GNSS and GRACE observations in South America main river basins: Amazon, Orinoco and Parana. In this area the hydrological effects are among the largest in the world mainly due to the river level variations. We present the results of time series analyses with spectral and principal component analysis (PCA) methods. We extract the dominant spatio-temporal annual mode. We also identify and characterize the spatio-temporal changes in the annual hydrology signal, which is the key to a better understanding of the water cycle variations of those major rivers. We demonstrate that it is crucial to take into account the river contribution in fluid signatures before investigating high-frequency variability and episodic events.

An empirical understanding of triple collocation evaluation measure

NASA Astrophysics Data System (ADS)

Scipal, Klaus; Doubkova, Marcela; Hegyova, Alena; Dorigo, Wouter; Wagner, Wolfgang

2013-04-01

Triple collocation method is an advanced evaluation method that has been used in the soil moisture field for only about half a decade. The method requires three datasets with an independent error structure that represent an identical phenomenon. The main advantages of the method are that it a) doesn't require a reference dataset that has to be considered to represent the truth, b) limits the effect of random and systematic errors of other two datasets, and c) simultaneously assesses the error of three datasets. The objective of this presentation is to assess the triple collocation error (Tc) of the ASAR Global Mode Surface Soil Moisture (GM SSM 1) km dataset and highlight problems of the method related to its ability to cancel the effect of error of ancillary datasets. In particular, the goal is to a) investigate trends in Tc related to the change in spatial resolution from 5 to 25 km, b) to investigate trends in Tc related to the choice of a hydrological model, and c) to study the relationship between Tc and other absolute evaluation methods (namely RMSE and Error Propagation EP). The triple collocation method is implemented using ASAR GM, AMSR-E, and a model (either AWRA-L, GLDAS-NOAH, or ERA-Interim). First, the significance of the relationship between the three soil moisture datasets was tested that is a prerequisite for the triple collocation method. Second, the trends in Tc related to the choice of the third reference dataset and scale were assessed. For this purpose the triple collocation is repeated replacing AWRA-L with two different globally available model reanalysis dataset operating at different spatial resolution (ERA-Interim and GLDAS-NOAH). Finally, the retrieved results were compared to the results of the RMSE and EP evaluation measures. Our results demonstrate that the Tc method does not eliminate the random and time-variant systematic errors of the second and the third dataset used in the Tc. The possible reasons include the fact a) that the TC method could not fully function with datasets acting at very different spatial resolutions, or b) that the errors were not fully independent as initially assumed.

Plate motions, Gondwana dinosaurs, Noah's arks, beached Viking funeral ships, ghost ships, and landspans.

PubMed

Jacobs, Louis L; Strganac, Christopher; Scotese, Christopher

2011-03-01

Gondwana landmasses have served as large-scale biogeographic Noah's Arks and Beached Viking Funeral Ships, as defined by McKenna. The latitudinal trajectories of selected Gondwana dinosaur localities were traced through time in order to evaluate their movement through climate zones relative to those in which they originally formed. The dispersal of fauna during the breakup of Gondwana may have been facilitated by the presence of offshelf islands forming landspans (sensu Iturralde-Vinent and MacPhee) in the Equatorial Atlantic Gateway and elsewhere.

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Sure, A.; Dikshit, O.

2017-12-01

Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

Stochastic Flow Cascades

NASA Astrophysics Data System (ADS)

Eliazar, Iddo I.; Shlesinger, Michael F.

2012-01-01

We introduce and explore a Stochastic Flow Cascade (SFC) model: A general statistical model for the unidirectional flow through a tandem array of heterogeneous filters. Examples include the flow of: (i) liquid through heterogeneous porous layers; (ii) shocks through tandem shot noise systems; (iii) signals through tandem communication filters. The SFC model combines together the Langevin equation, convolution filters and moving averages, and Poissonian randomizations. A comprehensive analysis of the SFC model is carried out, yielding closed-form results. Lévy laws are shown to universally emerge from the SFC model, and characterize both heavy tailed retention times (Noah effect) and long-ranged correlations (Joseph effect).

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Multi-geodetic characterization of the seasonal signal at the CERGA geodetic reference, France

NASA Astrophysics Data System (ADS)

Memin, A.; Viswanathan, V.; Fienga, A.; Santamaría-Gómez, A.; Boy, J. P.

2016-12-01

Crustal deformations due to surface-mass loading account for a significant part of the variability in geodetic time series. A perfect understanding of the loading signal observed by geodetic techniques should help in improving terrestrial reference frame (TRF) realizations. Yet, discrepancies between crustal motion estimates from models of surface-mass loading and observations are still too large so that no model is currently recommended by the IERS for reducing the data. We investigate the discrepancy observed in the seasonal variations of the CERGA station, South of France.We characterize the seasonal motions of the reference geodetic station CERGA from GNSS, SLR and LLR. We compare the station motion observed with GNSS and SLR and we estimate changes in the station-to-the-moon distance using an improved processing strategy. We investigate the consistency between these geodetic techniques and compare the observed station motion with that estimated using models of surface-mass change. In that regard, we compute atmospheric loading effects using surface pressure fields from ECMWF, assuming an ocean response according to the classical inverted barometer (IB) assumption, considered to be valid for periods typically exceeding a week. We also used general circulation ocean models (ECCO and GLORYS) forced by wind, heat and fresh water fluxes. The continental water storage is described using GLDAS/Noah and MERRA-land models.Using the surface-mass models, we estimate the amplitude of the seasonal vertical motion of the CERGA station ranging between 5 and 10 mm with a maximum reached in August, mostly due to hydrology. The horizontal seasonal motion of the station may reach up to 3 mm. Such a station motion should induce a change in the distance to the moon reaching up to 10 mm, large enough to be detected in LLR time series and compared to GNSS- and SLR-derived motion.

Estimates of Soil Moisture Using the Land Information System for Land Surface Water Storage: Case Study for the Western States Water Mission

NASA Astrophysics Data System (ADS)

Liu, P. W.; Famiglietti, J. S.; Levoe, S.; Reager, J. T., II; David, C. H.; Kumar, S.; Li, B.; Peters-Lidard, C. D.

2017-12-01

Soil moisture is one of the critical factors in terrestrial hydrology. Accurate soil moisture information improves estimation of terrestrial water storage and fluxes, that is essential for water resource management including sustainable groundwater pumping and agricultural irrigation practices. It is particularly important during dry periods when water stress is high. The Western States Water Mission (WSWM), a multiyear mission project of NASA's Jet Propulsion Laboratory, is operated to understand and estimate quantities of the water availability in the western United States by integrating observations and measurements from in-situ and remote sensing sensors, and hydrological models. WSWM data products have been used to assess and explore the adverse impacts of the California drought (2011-2016) and provide decision-makers information for water use planning. Although the observations are often more accurate, simulations using land surface models can provide water availability estimates at desired spatio-temporal scales. The Land Information System (LIS), developed by NASA's Goddard Space Flight Center, integrates developed land surface models and data processing and management tools, that enables to utilize the measurements and observations from various platforms as forcings in the high performance computing environment to forecast the hydrologic conditions. The goal of this study is to implement the LIS in the western United States for estimates of soil moisture. We will implement the NOAH-MP model at the 12km North America Land Data Assimilation System grid and compare to other land surface models included in the LIS. Findings will provide insight into the differences between model estimates and model physics. Outputs from a multi-model ensemble from LIS can also be used to enhance estimated reliability and provide quantification of uncertainty. We will compare the LIS-based soil moisture estimates to the SMAP enhanced 9 km soil moisture product to understand the mechanistic differences between the model and observation. These outcomes will contribute to the WSWM for providing robust products.

Dual Assimilation of Microwave and Thermal-Infrared Satellite Observations of Soil Moisture into NLDAS for Improved Drought Monitoring

NASA Astrophysics Data System (ADS)

Hain, C.; Crow, W. T.; Anderson, M. C.; Zhan, X.; Wardlow, B.; Svoboda, M. D.; Mecikalski, J. R.

2011-12-01

Our research group is currently developing an operational data assimilation (DA) system for the optimal assimilation of thermal infrared (TIR) and microwave (MV) soil moisture (SM) and insertion of near real-time green vegetation fraction (GVF) into the Noah land-surface model component of the National Land Data Assimilation System (NLDAS). NLDAS produces the hydrologic products (e.g. soil moisture, evapotranspiration, and runoff) used by NCEP for operational drought monitoring, but these products are sensitive to model input errors in soil texture (affecting infiltration rates) and prescribed precipitation rates. Periodic updates of SM state variables in LSMs achieved by assimilating diagnostic moisture information retrieved using satellite remote sensing have been shown to compensate for model errors and result in improved hydrologic output. The work proposed here will build on a project currently funded under the Climate Test Bed Program entitled "A GOES Thermal-Based Drought Early Warning Index for NIDIS", which is developing an operational TIR SM index (Evaporative Stress Index; ESI) based on maps of the ratio of actual to potential ET (fPET) generated with the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm. The research team has demonstrated that diagnostic information about SM and evapotranspiration (ET) from MW and TIR remote sensing can significantly reduce SM drifts in LSMs such as Noah. The two different SM retrievals have been shown to be quite complementary: TIR provides relatively high spatial (down to 100 m) and low temporal resolution (due to cloud cover) retrievals over a wide range of GVF, while MW provides relatively low spatial (25 to 60 km) and high temporal resolution (can retrieve through cloud cover), but only over areas with low GVF. Furthermore, MW retrievals are sensitive to SM only in the first few centimeters of the soil profile, while TIR provides information about SM conditions integrated over the full root-zone, reflected in the observed canopy temperature. The added value of TIR over MW alone is most significant in areas of moderate to dense vegetation cover where MW retrievals have very little sensitivity to SM at any depth. Finally, climatological estimates of GVF currently used in the operational NLDAS are not always representative of observed seasonal and intra-seasonal GVF conditions, especially in regions experiencing drought conditions. A detailed methodology of the assimilation system will be presented along with an analysis of initial results, with an emphasis on comparisons with in-situ SM observations and standard drought metrics.

The Impact of Infiltration Losses and Model Resolution on the Simulated Hydrometeorological Response of a Semi-Arid Catchment

NASA Astrophysics Data System (ADS)

Mitchell, M. F.; Goodrich, D. C.; Gochis, D. J.; Lahmers, T. M.

2017-12-01

In semi-arid environments with complex terrain, redistribution of moisture occurs through runoff, stream infiltration, and regional groundwater flow. In semi-arid regions, stream infiltration has been shown to account for 10-40% of total recharge in high runoff years. These processes can potentially significantly alter land-atmosphere interactions through changes in sensible and latent heat release. However, currently, their overall impact is still unclear as historical model simulations generally made use of a coarse grid resolution, where these smaller-scale processes were either parameterized or not accounted for. To improve our understanding on the importance of stream infiltration and our ability to represent them in a coupled land-atmosphere model, this study focuses on the Walnut Gulch Experimental Watershed (WGEW) and Long-Term Agro-ecosystem Research (LTAR) site, surrounding the city of Tombstone, AZ. High-resolution surface precipitation, meteorological forcing and distributed runoff measurements have been obtained in WGEW since the 1960s. These data will be used as input for the spatially distributed WRF-Hydro model, a spatially distributed hydrological model that uses the NOAH-MP land surface model. Recently, we have implemented an infiltration loss scheme to WRF-Hydro. We will present the performance of WRF-Hydro to account for stream infiltration by comparing model simulation with in-situ observations. More specifically, as the performance of the model simulations has been shown to depend on the used model grid resolution, in the current work results will present WRF-Hydro simulations obtained at different pixel resolution (10-1000m).

Simulating land-atmosphere feedbacks and response to widespread forest disturbance: The role of lower boundary configuration and dynamic water table in meteorological modeling

NASA Astrophysics Data System (ADS)

Forrester, M.; Maxwell, R. M.; Bearup, L. A.; Gochis, D.

2017-12-01

Numerical meteorological models are frequently used to diagnose land-atmosphere interactions and predict large-scale response to extreme or hazardous events, including widespread land disturbance or perturbations to near-surface moisture. However, few atmospheric modeling platforms consider the impact that dynamic groundwater storage, specifically 3D subsurface flow, has on land-atmosphere interactions. In this study, we use the Weather Research and Forecasting (WRF) mesoscale meteorological model to identify ecohydrologic and land-atmosphere feedbacks to disturbance by the mountain pine beetle (MPB) over the Colorado Headwaters region. Disturbance simulations are applied to WRF with various lower boundary configurations: Including default Noah land surface model soil moisture representation; a version of WRF coupled to ParFlow (PF), an integrated groundwater-surface water model that resolves variably saturated flow in the subsurface; and WRF coupled to PF in a static water table version, simulating only vertical and no lateral subsurface flow. Our results agree with previous literature showing MPB-induced reductions in canopy transpiration in all lower boundary scenarios, as well as energy repartitioning, higher water tables, and higher planetary boundary layer over infested regions. Simulations show that expanding from local to watershed scale results in significant damping of MPB signal as unforested and unimpacted regions are added; and, while deforestation appears to have secondary feedbacks to planetary boundary layer and convection, these slight perturbations to cumulative summer precipitation are insignificant in the context of ensemble methodologies. Notably, the results suggest that groundwater representation in atmospheric modeling affects the response intensity of a land disturbance event. In the WRF-PF case, energy and atmospheric processes are more sensitive to disturbance in regions with higher water tables. Also, when dynamic subsurface hydrology is removed, WRF simulates a greater response to MPB at the land-atmosphere interface, including greater changes to daytime skin temperature, Bowen ratio and near-surface humidity. These findings highlight lower boundary representations in computational meteorology and numerical land-atmosphere modeling.

A numerical study of the effect of irrigation on land-atmosphere interactions in a spring wheat cropland in India using a coupled atmosphere-crop growth dynamics model

NASA Astrophysics Data System (ADS)

Kumari, S.; Sharma, P.; Srivastava, A.; Rastogi, D.; Sehgal, V. K.; Dhakar, R.; Roy, S. B.

2017-12-01

Vegetation dynamics and surface meteorology are tightly coupled through the exchange of momentum, moisture and heat between the land surface and the atmosphere. In this study, we use a recently developed coupled atmosphere-crop growth dynamics model to study these exchanges and their effects in a spring wheat cropland in northern India. In particular, we investigate the role of irrigation in controlling crop growth rates, surface meteorology, and sensible and latent heat fluxes. The model is developed by implementing a crop growth module based on the Simple and Universal Crop growth Simulator (SUCROS) model in the Weather Research Forecasting (WRF) mesoscale atmospheric model. The crop module calculates photosynthesis rates, carbon assimilation, and biomass partitioning as a function of environmental factors and crop development stage. The leaf area index (LAI) and root depth calculated by the crop module is then fed to the Noah-MP land module of WRF to calculate land-atmosphere fluxes. The crop model is calibrated using data from an experimental spring wheat crop site in the Indian Agriculture Research Institute. The coupled model is capable of simulating the observed spring wheat phenology. Irrigation is simulated by changing the soil moisture levels from 50% - 100% of field capacity. Results show that the yield first increases with increasing soil moisture and then starts decreasing as we further increase the soil moisture. Yield attains its maximum value with soil moisture at the level of 60% water of FC. At this level, high LAI values lead to a decrease in the Bowen Ratio because more energy is transferred to the atmosphere as latent heat rather than sensible heat resulting in a cooling effect on near-surface air temperatures. Apart from improving simulation of land-atmosphere interactions, this coupled modeling approach can form the basis for the seamless crop yield and seasonal scale weather outlook prediction system.

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

NASA Technical Reports Server (NTRS)

Kumar, Sujay; Santanello, Joseph; Peters-Lidard, Christa; Harrison, Ken

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

Multi-geodetic characterization of the seasonal signal at the CERGA geodetic reference station, France

NASA Astrophysics Data System (ADS)

Mémin, Anthony; Viswanathan, Vishnu; Fienga, Agnes; Santamarìa-Gómez, Alvaro; Boy, Jean-Paul; Cavalié, Olivier; Deleflie, Florent; Exertier, Pierre; Bernard, Jean-Daniel; Hinderer, Jacques

2017-04-01

Crustal deformations due to surface-mass loading account for a significant part of the variability in geodetic time series. A perfect understanding of the loading signal observed by geodetic techniques should help in improving terrestrial reference frame (TRF) realizations. Yet, discrepancies between crustal motion estimates from models of surface-mass loading and observations are still too large so that no model is currently recommended by the IERS for reducing the observations. We investigate the discrepancy observed in the seasonal variations of the position at the CERGA station, South of France. We characterize the seasonal motions of the reference geodetic station CERGA from GNSS, SLR, LLR and InSAR. We investigate the consistency between the station motions deduced from these geodetic techniques and compare the observed station motion with that estimated using models of surface-mass change. In that regard, we compute atmospheric loading effects using surface pressure fields from ECMWF, assuming an ocean response according to the classical inverted barometer (IB) assumption, considered to be valid for periods typically exceeding a week. We also used general circulation ocean models (ECCO and GLORYS) forced by wind, heat and fresh water fluxes. The continental water storage is described using GLDAS/Noah and MERRA-land models. Using the surface-mass models, we estimate that the seasonal signal due to loading deformation at the CERGA station is about 8-9, 1-2 and 1-2 mm peak-to-peak in Up, North and East component, respectively. There is a very good correlation between GPS observations and non-tidal loading predicted deformation due to atmosphere, ocean and hydrology which is the main driver of seasonal signal at CERGA. Despite large error bars, LLR observations agree reasonably well with GPS and non-tidal loading predictions in Up component. Local deformation as observed by InSAR is very well correlated with GPS observations corrected for non-tidal loading. Finally, we estimate local mass changes using the absolute gravity measurement campaigns available at the station and the global models of surface-mass change. We compute the induced station motion that we compare with the local deformation observed by InSAR and GPS.

Comparison of Prognostic and Diagnostic Approaches to Modeling Evapotranspiration in the Nile River Basin

NASA Astrophysics Data System (ADS)

Yilmaz, M.; Anderson, M. C.; Zaitchik, B. F.; Crow, W. T.; Hain, C.; Ozdogan, M.; Chun, J. A.

2012-12-01

Actual evapotranspiration (ET) can be estimated using both prognostic and diagnostic modeling approaches, providing independent yet complementary information for hydrologic applications. Both approaches have advantages and disadvantages. When provided with temporally continuous atmospheric forcing data, prognostic models offer continuous sub-daily ET information together with the full set of water and energy balance fluxes and states (i.e. soil moisture, runoff, sensible and latent heat). On the other hand, the diagnostic modeling approach provides ET estimates over regions where reliable information about available soil water is not known (e.g., due to irrigation practices or shallow ground water levels not included in the prognostic model structure, unknown soil texture or plant rooting depth, etc). Prognostic model-based ET estimates are of great interest whenever consistent and complete water budget information is required or when there is a need to project ET for climate or land use change scenarios. Diagnostic models establish a stronger link to remote sensing observations, can be applied in regions with limited or questionable atmospheric forcing data, and provide valuable observation-derived information about the current land-surface state. Analysis of independently obtained ET estimates is particularly important in data poor regions. Such comparisons can help to reduce the uncertainty in the modeled ET estimates and to exclude outliers based on physical considerations. The Nile river basin is home to tens of millions of people whose daily life depends on water extracted from the river Nile. Yet the complete basin scale water balance of the Nile has been studied only a few times, and the temporal and the spatial distribution of hydrological fluxes (particularly ET) are still a subject of active research. This is due in part to a scarcity of ground-based station data for validation. In such regions, comparison between prognostic and diagnostic model output may be a valuable model evaluation tool. Motivated by the complementary information that exists in prognostic and diagnostic energy balance modeling, as well as the need for evaluation of water consumption estimates over the Nile basin, the purpose of this study is to 1) better describe the conceptual differences between prognostic and diagnostic modeling, 2) present the potential for diagnostic models to capture important hydrologic features that are not explicitly represented in prognostic model, 3) explore the differences in these two approaches over the Nile Basin, where ground data are sparse and transnational data sharing is unreliable. More specifically, we will compare output from the Noah prognostic model and the Atmosphere-Land Exchange Inverse (ALEXI) diagnostic model generated over ground truth data-poor Nile basin. Preliminary results indicate spatially, temporally, and magnitude wise consistent flux estimates for ALEXI and NOAH over irrigated Delta region, while there are differences over river-fed wetlands.

Method and Early Results of Applying the Global Land Data Assimilation System (GLDAS) in the Third Global Reanalysis of NCEP

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Yang, R.; Kumar, S.; Geiger, J.; Xie, P.

2008-05-01

Over the past several years, the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) of the U.S. National Weather Service has developed a Global Land Data Assimilation System (GLDAS). For its computational infrastructure, the GLDAS applies the NASA Land Information System (LIS), developed by the Hydrological Science Branch of NASA Goddard Space Flight Center. The land model utilized in the NCEP GLDAS is the NCEP Noah Land Surface Model (Noah LSM). This presentation will 1) describe how the GLDAS component has been included in the development of NCEP's third global reanalysis (with special attention to the input sources of global precipitation), and 2) will present results from the GLDAS component of pilot tests of the new NCEP global reanalysis. Unlike NCEP's past two global reanalysis projects, this new NCEP global reanalysis includes both a global land data assimilation system (GLDAS) and a global ocean data assimilation system (GODAS). The new global reanalysis will span 30-years (1979-2008) and will include a companion realtime operational component. The atmospheric, ocean, and land states of this global reanalysis will provide the initial conditions for NCEP's 3rd- generation global coupled Climate Forecast System (CFS). NCEP is now preparing to launch a 28-year seasonal reforecast project with its new CFS, to provide the reforecast foundation for operational NCEP seasonal climate forecasts using the new CFS. Together, the new global reanalysis and companion CFS reforecasts constitute what NCEP calls the Climate Forecast System Reanalysis and Reforecast (CFSRR) project. Compared to the previous two generations of NCEP global reanalysis, the hallmark of the GLDAS component of CFSRR is GLDAS use of global analyses of observed precipitation to drive the land surface component of the reanalysis (rather than the typical reanalysis approach of using precipitation from the assimilating background atmospheric model). Specifically, the GLDAS merges two global analyses of observed precipitation produced by the Climate Prediction Center (CPC) of NCEP, as follows: 1) a new CPC daily gauge-only land-only global precipitation analysis at 0.5-degree resolution and 2) the well-known CPC CMAP global 2.0 x 2.5 degree 5-day precipitation analysis, which utilizes satellite estimates of precipitation, as well as some gauge observations. The presentation will describe how these two analyses are merged with latitude-dependent weights that favor the gauge-only analysis in mid-latitudes and the satellite-dominated CMAP analysis in tropical latitudes. Finally, we will show some impacts of using GLDAS to initialize the land states of seasonal CFS reforecasts, versus using the previous generation of NCEP global reanalysis as the source for CFS initial land states.

Distributions of extreme bursts above thresholds in a fractional Lévy toy model of natural complexity.

NASA Astrophysics Data System (ADS)

Watkins, Nicholas; Chapman, Sandra; Rosenberg, Sam; Credgington, Dan; Sanchez, Raul

2010-05-01

In 2 far-sighted contributions in the 1960s Mandelbrot showed the ubiquity of both non-Gaussian fluctuations and long-ranged temporal memory (the "Noah" and "Joseph" effects, respectively) in the natural and man-made worlds. Much subsequent work in complexity science has contributed to the physical underpinning of these effects, particularly in cases where complex interactions in a system cause a driven or random perturbation to be nonlinearly amplified in amplitude and/or spread out over a wide range of frequencies. In addition the modelling of catastrophes has begun to incorporate the insights which these approaches have offered into the likelihood of extreme and long-lived fluctuations. I will briefly survey how the application of the above ideas in the earth system has been a key focus and motivation of research into natural complexity at BAS [e.g. Watkins & Freeman, Science, 2008; Edwards et al, Nature, 2007]. I will then discuss in detail a standard toy model (linear fractional stable motion, LFSM) which combines the Noah and Joseph effects in a controllable way and explain how it differs from the widely used continuous time random walk. I will describe how LFSM is being used to explore the interplay of the above two effects in the distribution of bursts above thresholds. I will describe ongoing work to improve the accuracy of maximum likelihood-based estimation of burst size and waiting time distributions for LFSM first reported in [Watkins et al, PRE, 2009]; and will also touch on similar work for multifractal models [Watkins et al, PRL comment, 2009].

Enabling NLDAS-2 Anomaly Analysis Using Giovanni

NASA Astrophysics Data System (ADS)

Loeser, C.; Rui, H.; Teng, W. L.; Vollmer, B.; Mocko, D. M.

2017-12-01

A newly implemented feature in Giovanni (GES DISC Interactive Online Visualization and Analysis Interface) allows users to explore and visualize anomaly data from the NLDAS-2 Primary Forcing and Noah model data sets. For a given measurement and location, an anomaly describes how conditions for a particular time period compare to normal conditions, based on long-term averages. Analyzing anomalies is important for monitoring droughts, determining weather trends, and studying land surface processes relevant for meteorology, hydrology, and climate. Using Giovanni to analyze anomalies for NLDAS-2 data allows for these studies to be efficiently conducted for the central North American region. Phase 2 of NLDAS (NLDAS-2) currently runs at an 1/8th degree resolution, in near-real time, with data sets extending back to January 1979. NLDAS-2 provides data for soil moisture, precipitation, temperature, and other hydrology measurements. Hourly, monthly, and 30-year (1980-2009) monthly climatology data are available for several land surface models and forcing data sets. The Giovanni anomaly tool calculates monthly anomalies, for a given user-defined variable, as the difference between the NLDAS-2 monthly climatology data and the monthly data. The resulting anomaly describes how a chosen month compares to the 30-year monthly average. The presentation will demonstrate the capabilities and usefulness of Giovanni's anomaly tool, detail the recently added NLDAS-2 variables for which anomalies are available, and show how users can access the data.

Enabling NLDAS-2 Anomaly Analysis Using Giovanni

NASA Technical Reports Server (NTRS)

Loeser, Carlee; Rui, Hualan; Teng, William; Vollmer, Bruce; Mocko, David

2017-01-01

A newly implemented feature in Giovanni (GES DISC Interactive Online Visualization and Analysis Interface) allows users to explore and visualize anomaly data from the NLDAS-2 Primary Forcing and Noah model data sets. For a given measurement and location, an anomaly describes how conditions for a particular time period compare to normal conditions, based on long-term averages. Analyzing anomalies is important for monitoring droughts, determining weather trends, and studying land surface processes relevant for meteorology, hydrology, and climate. Using Giovanni to analyze anomalies for NLDAS-2 data allows for these studies to be efficiently conducted for the central North American region. Phase 2 of NLDAS (NLDAS-2) currently runs at an 1/8th degree resolution, in near-real time, with data sets extending back to January 1979. NLDAS-2 provides data for soil moisture, precipitation, temperature, and other hydrology measurements. Hourly, monthly, and 30-year (1980-2009) monthly climatology data are available for several land surface models and forcing data sets. The Giovanni anomaly tool calculates monthly anomalies, for a given user-defined variable, as the difference between the NLDAS-2 monthly climatology data and the monthly data. The resulting anomaly describes how a chosen month compares to the 30-year monthly average. The presentation will demonstrate the capabilities and usefulness of Giovanni's anomaly tool, detail the recently added NLDAS-2 variables for which anomalies are available, and show how users can access the data.

The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation

NASA Astrophysics Data System (ADS)

Shuttleworth, J.; Rosolem, R.; Zreda, M.; Franz, T.

2013-08-01

Soil moisture status in land surface models (LSMs) can be updated by assimilating cosmic-ray neutron intensity measured in air above the surface. This requires a fast and accurate model to calculate the neutron intensity from the profiles of soil moisture modeled by the LSM. The existing Monte Carlo N-Particle eXtended (MCNPX) model is sufficiently accurate but too slow to be practical in the context of data assimilation. Consequently an alternative and efficient model is needed which can be calibrated accurately to reproduce the calculations made by MCNPX and used to substitute for MCNPX during data assimilation. This paper describes the construction and calibration of such a model, COsmic-ray Soil Moisture Interaction Code (COSMIC), which is simple, physically based and analytic, and which, because it runs at least 50 000 times faster than MCNPX, is appropriate in data assimilation applications. The model includes simple descriptions of (a) degradation of the incoming high-energy neutron flux with soil depth, (b) creation of fast neutrons at each depth in the soil, and (c) scattering of the resulting fast neutrons before they reach the soil surface, all of which processes may have parameterized dependency on the chemistry and moisture content of the soil. The site-to-site variability in the parameters used in COSMIC is explored for 42 sample sites in the COsmic-ray Soil Moisture Observing System (COSMOS), and the comparative performance of COSMIC relative to MCNPX when applied to represent interactions between cosmic-ray neutrons and moist soil is explored. At an example site in Arizona, fast-neutron counts calculated by COSMIC from the average soil moisture profile given by an independent network of point measurements in the COSMOS probe footprint are similar to the fast-neutron intensity measured by the COSMOS probe. It was demonstrated that, when used within a data assimilation framework to assimilate COSMOS probe counts into the Noah land surface model at the Santa Rita Experimental Range field site, the calibrated COSMIC model provided an effective mechanism for translating model-calculated soil moisture profiles into aboveground fast-neutron count when applied with two radically different approaches used to remove the bias between data and model.

A Fractional Differential Kinetic Equation and Applications to Modelling Bursts in Turbulent Nonlinear Space Plasmas

NASA Astrophysics Data System (ADS)

Watkins, N. W.; Rosenberg, S.; Sanchez, R.; Chapman, S. C.; Credgington, D.

2008-12-01

Since the 1960s Mandelbrot has advocated the use of fractals for the description of the non-Euclidean geometry of many aspects of nature. In particular he proposed two kinds of model to capture persistence in time (his Joseph effect, common in hydrology and with fractional Brownian motion as the prototype) and/or prone to heavy tailed jumps (the Noah effect, typical of economic indices, for which he proposed Lévy flights as an exemplar). Both effects are now well demonstrated in space plasmas, notably in the turbulent solar wind. Models have, however, typically emphasised one of the Noah and Joseph parameters (the Lévy exponent μ and the temporal exponent β) at the other's expense. I will describe recent work in which we studied a simple self-affine stable model-linear fractional stable motion, LFSM, which unifies both effects and present a recently-derived diffusion equation for LFSM. This replaces the second order spatial derivative in the equation of fBm with a fractional derivative of order μ, but retains a diffusion coefficient with a power law time dependence rather than a fractional derivative in time. I will also show work in progress using an LFSM model and simple analytic scaling arguments to study the problem of the area between an LFSM curve and a threshold. This problem relates to the burst size measure introduced by Takalo and Consolini into solar-terrestrial physics and further studied by Freeman et al [PRE, 2000] on solar wind Poynting flux near L1. We test how expressions derived by other authors generalise to the non-Gaussian, constant threshold problem. Ongoing work on extension of these LFSM results to multifractals will also be discussed.

Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

2016-01-01

Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

NASA Technical Reports Server (NTRS)

White, Kristopher D.; Case, Jonathan L.

2014-01-01

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

Why the predictions for monsoon rainfall fail?

NASA Astrophysics Data System (ADS)

Lee, J.

2016-12-01

To be in line with the Global Land/Atmosphere System Study (GLASS) of the Global Energy and Water Cycle Experiment (GEWEX) international research scheme, this study discusses classical arguments about the feedback mechanisms between land surface and precipitation to improve the predictions of African monsoon rainfall. In order to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, several data sets will be presented. First, in-situ soil moisture field measurements acquired by the AMMA field campaign will be shown together with rain gauge data. This data set will validate various model and satellite data sets such as NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models, SMOS soil moisture. To relate soil moisture with precipitation, two approaches are employed: one approach makes a direct comparison between the spatial distributions of soil moisture as an absolute value and rainfall, while the other measures a temporal evolution of the consecutive dry days (i.e. a relative change within the same soil moisture data set over time) and rainfall occurrences. Consecutive dry days shows consistent results of a negative feedback between soil moisture and rainfall across various data sets, contrary to the direct comparison of soil moisture state. This negative mechanism needs attention, as most climate models usually focus on a positive feedback only. The approach of consecutive dry days takes into account the systematic errors in satellite observations, reminding us that it may cause the misinterpretation to directly compare model with satellite data, due to their difference in data retrievals. This finding is significant, as the climate indices employed by the Intergovernmental Panel on Climate Change (IPCC) modelling archive are based on the atmospheric variable rathr than land.

Sensitivity of volatile organic compounds (VOCs) and ozone to land surface processes and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, C.; Huang, M.; Fast, J. D.; Berg, L. K.; Qian, Y.; Guenther, A. B.; Gu, D.; Shrivastava, M. B.; Liu, Y.; Walters, S.; Jin, J.

2014-12-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect secondary organic aerosol (SOA) formation and ultimately aerosol radiative forcing. These uncertainties result from many factors, including coupling strategy between biogenic emissions and land-surface schemes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (VOCs). In this study, sensitivity experiments are conducted using the Weather Research and Forecasting model with chemistry (WRF-Chem) to examine the sensitivity of simulated VOCs and ozone to land surface processes and vegetation distributions in California. The measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010 provide a good opportunity to evaluate the simulations. First, the biogenic VOC emissions in the WRF-Chem simulations with the two land surface schemes, Noah and CLM4, are estimated by the Model of Emissions of Gases and Aerosols from Nature version one (MEGANv1), which has been publicly released and widely used with WRF-Chem. The impacts of land surface processes on estimating biogenic VOC emissions and simulating VOCs and ozone are investigated. Second, in this study, a newer version of MEGAN (MEGANv2.1) is coupled with CLM4 as part of WRF-Chem to examine the sensitivity of biogenic VOC emissions to the MEGAN schemes used and determine the importance of using a consistent vegetation map between a land surface scheme and the biogenic VOC emission scheme. Specifically, MEGANv2.1 is embedded into the CLM4 scheme and shares a consistent vegetation map for estimating biogenic VOC emissions. This is unlike MEGANv1 in WRF-Chem that uses a standalone vegetation map that differs from what is used in land surface schemes. Furthermore, we examine the impact of vegetation distribution on simulating VOCs and ozone by comparing coupled WRF-Chem-CLM-MEGANv2.1 simulations using multiple vegetation maps.

Urban Canopy Effects in Regional Climate Simulations - An Inter-Model Comparison

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.; Karlicky, J.

2017-12-01

To assess the impact of cities and urban surfaces on climate, the modeling approach is often used with inclusion of urban parameterization in land-surface interactions. This is especially important when going to higher resolution, which is common trend both in operational weather prediction and regional climate modelling. Model description of urban canopy related meteorological effects can, however, differ largely given especially the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. To assess this uncertainty is important for adaptation and mitigation measures often applied in the big cities, especially in connection to climate change perspective, which is one of the main task of the new project OP-PPR Proof of Concept UK. In this study we contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two regional climate models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Effects of cities on urban and remote areas were evaluated. There are some differences in sensitivity of individual canopy model implementations to the UHI effects, depending on season and size of the city as well. Effect of reducing diurnal temperature range in cities (around 2 °C in summer mean) is noticeable in all simulations, independent to urban parameterization type and model, due to well-known warmer summer city nights. For the adaptation and mitigation purposes, rather than the average urban heat island intensity the distribution of it is more important providing the information on extreme UHI effects, e.g. during heat waves. We demonstrate that for big central European cities this effect can approach 10°C, even for not so big ones these extreme effects can go above 5°C.

Hydrologic Modeling at the National Water Center: Operational Implementation of the WRF-Hydro Model to support National Weather Service Hydrology

NASA Astrophysics Data System (ADS)

Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Fall, G. M.; Feng, X.; Fresch, M. A.; Gourley, J. J.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Smith, M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.; Zhang, Y.

2015-12-01

The National Weather Service (NWS) National Water Center(NWC) is collaborating with the NWS National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to implement a first-of-its-kind operational instance of the Weather Research and Forecasting (WRF)-Hydro model over the Continental United States (CONUS) and contributing drainage areas on the NWS Weather and Climate Operational Supercomputing System (WCOSS) supercomputer. The system will provide seamless, high-resolution, continuously cycling forecasts of streamflow and other hydrologic outputs of value from both deterministic- and ensemble-type runs. WRF-Hydro will form the core of the NWC national water modeling strategy, supporting NWS hydrologic forecast operations along with emergency response and water management efforts of partner agencies. Input and output from the system will be comprehensively verified via the NWC Water Resource Evaluation Service. Hydrologic events occur on a wide range of temporal scales, from fast acting flash floods, to long-term flow events impacting water supply. In order to capture this range of events, the initial operational WRF-Hydro configuration will feature 1) hourly analysis runs, 2) short-and medium-range deterministic forecasts out to two day and ten day horizons and 3) long-range ensemble forecasts out to 30 days. All three of these configurations are underpinned by a 1km execution of the NoahMP land surface model, with channel routing taking place on 2.67 million NHDPlusV2 catchments covering the CONUS and contributing areas. Additionally, the short- and medium-range forecasts runs will feature surface and sub-surface routing on a 250m grid, while the hourly analyses will feature this same 250m routing in addition to nudging-based assimilation of US Geological Survey (USGS) streamflow observations. A limited number of major reservoirs will be configured within the model to begin to represent the first-order impacts of streamflow regulation.

Urban effects on regional climate: a case study in the Phoenix and Tucson ‘sun’ corridor

USGS Publications Warehouse

Zhao Yang,; Francina Dominguez,; Hoshin Gupta,; Xubin Zeng,; Norman, Laura M.

2016-01-01

Land use and land cover change (LULCC) due to urban expansion alter the surface albedo, heat capacity, and thermal conductivity of the surface. Consequently, the energy balance in urban regions is different from that of natural surfaces. To evaluate the changes in regional climate that could arise due to projected urbanization in the Phoenix-Tucson corridor, Arizona, we applied the coupled WRF-NOAH-UCM (which includes a detailed urban radiation scheme) to this region. Land cover changes were represented using land cover data for 2005 and projections to 2050, and historical North American Regional Reanalysis (NARR) data were used to specify the lateral boundary conditions. Results suggest that temperature changes will be well defined, reflecting the urban heat island (UHI) effect within areas experiencing LULCC. Changes in precipitation are less robust, but seem to indicate reductions in precipitation over the mountainous regions northeast of Phoenix and decreased evening precipitation over the newly-urbanized area.

Regional inversion of GRACE data for continental water mass time-variations. Comparison with global hydrology models, classical spherical harmonics and "mascons" solutions

NASA Astrophysics Data System (ADS)

Seoane, L.; Ramillien, G.; Frappart, F.; Biancale, R.; Gratton, S.; Bourgogne, S.

2010-12-01

Time series of 2°-by-2° constrained/unconstrained GRACE geoid solutions have been computed with a 10-day resolution by using a new regional method recently implemented at GRGS (Toulouse, France). This approach uses the dynamical orbit analysis of GRACE Level-1 measurements, and specially accurate along-track KBRR residuals to estimate the continental water mass changes over large geographical regions. For validation, our GRACE-derived regional maps are compared to: (1) the global hydrological model outputs (WGHM, LaD, NOAH), (2) the NASA "mascons" solutions based on spherical harmonics and (3) the global solutions produced by GRGS and CSR, GFZ, JPL filtered with different methodologies (Gaussian, destriped and smoothed, ICA). In this study, we focus on the annual time scale of water mass redistributions occuring in drainage basins like Amazon or Congo. Each 2°-averaged surface element is characterized by its seasonal amplitude and phase. Even if the all sources are expected to provide quite comparable results for the continental water cycle, we suspect the residual differences are from smoothing effects of the spatial constraints included in the "mascons" solutions and the underestimating the seasonal amplitudes by global hydrological models.

The consecutive dry days to trigger rainfall over West Africa

NASA Astrophysics Data System (ADS)

Lee, J. H.

2018-01-01

In order to resolve contradictions in addressing a soil moisture-precipitation feedback mechanism over West Africa and to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, we first validated various data sets (SMOS satellite soil moisture observations, NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models) with the Analyses Multidisciplinaires de la Mousson Africaine (AMMA) field campaign data. Based on this analysis, it was suggested that biases of data sets might cause contradictions in studying mechanisms. Thus, by taking into account uncertainties in data, it was found that the approach of consecutive dry days (i.e. a relative comparison of time-series) showed consistency across various data sets, while the direct comparison approach for soil moisture state and rainfall did not. Thus, it was discussed that it may be difficult to directly relate rain with soil moisture as the absolute value, however, it may be reasonable to compare a temporal progress of the variables. Based upon the results consistently showing a positive relationship between the consecutive dry days and rainfall, this study supports a negative feedback often neglected by climate model structure. This approach is less sensitive to interpretation errors arising from systematic errors in data sets, as this measures a temporal gradient of soil moisture state.

Simulations of wind erosion along the Qinghai-Tibet Railway in north-central Tibet

NASA Astrophysics Data System (ADS)

Jiang, Yingsha; Gao, Yanhong; Dong, Zhibao; Liu, Benli; Zhao, Lin

2018-06-01

Wind erosion along the Qinghai-Tibet Railway causes sand hazard and poses threats to the safety of trains and passengers. A coupled land-surface erosion model (Noah-MPWE) was developed to simulate the wind erosion along the railway. Comparison with the data from the 137Cs isotope analysis shows that this coupled model could simulate the mean erosion amount reasonably. The coupled model was then applied to eight sites along the railway to investigate the wind-erosion distribution and variations from 1979 to 2012. Factors affecting wind erosion spatially and temporally were assessed as well. Majority wind erosion occurs in the non-monsoon season from December to April of the next year except for the site located in desert. The region between Wudaoliang and Tanggula has higher wind erosion occurrences and soil lose amount because of higher frequency of strong wind and relatively lower soil moisture than other sites. Inter-annually, all sites present a significant decreasing trend of annual soil loss with an average rate of -0.18 kg m-2 a-1 in 1979-2012. Decreased frequency of strong wind, increased precipitation and soil moisture contribute to the reduction of wind erosion in 1979-2012. Snow cover duration and vegetation coverage also have great impact on the occurrence of wind erosion.

Land Surface Modeling Applications for Famine Early Warning

NASA Astrophysics Data System (ADS)

McNally, A.; Verdin, J. P.; Peters-Lidard, C. D.; Arsenault, K. R.; Wang, S.; Kumar, S.; Shukla, S.; Funk, C. C.; Pervez, M. S.; Fall, G. M.; Karsten, L. R.

2015-12-01

AGU 2015 Fall Meeting Session ID#: 7598 Remote Sensing Applications for Water Resources Management Land Surface Modeling Applications for Famine Early Warning James Verdin, USGS EROS Christa Peters-Lidard, NASA GSFC Amy McNally, NASA GSFC, UMD/ESSIC Kristi Arsenault, NASA GSFC, SAIC Shugong Wang, NASA GSFC, SAIC Sujay Kumar, NASA GSFC, SAIC Shrad Shukla, UCSB Chris Funk, USGS EROS Greg Fall, NOAA Logan Karsten, NOAA, UCAR Famine early warning has traditionally required close monitoring of agro-climatological conditions, putting them in historical context, and projecting them forward to anticipate end-of-season outcomes. In recent years, it has become necessary to factor in the effects of a changing climate as well. There has also been a growing appreciation of the linkage between food security and water availability. In 2009, Famine Early Warning Systems Network (FEWS NET) science partners began developing land surface modeling (LSM) applications to address these needs. With support from the NASA Applied Sciences Program, an instance of the Land Information System (LIS) was developed to specifically support FEWS NET. A simple crop water balance model (GeoWRSI) traditionally used by FEWS NET took its place alongside the Noah land surface model and the latest version of the Variable Infiltration Capacity (VIC) model, and LIS data readers were developed for FEWS NET precipitation forcings (NOAA's RFE and USGS/UCSB's CHIRPS). The resulting system was successfully used to monitor and project soil moisture conditions in the Horn of Africa, foretelling poor crop outcomes in the OND 2013 and MAM 2014 seasons. In parallel, NOAA created another instance of LIS to monitor snow water resources in Afghanistan, which are an early indicator of water availability for irrigation and crop production. These successes have been followed by investment in LSM implementations to track and project water availability in Sub-Saharan Africa and Yemen, work that is now underway. Adoption of LSM and data assimilation technology has enabled FEWS NET to take greater advantage of remote sensing observations to robustly estimate key agro-climatological states, like soil moisture and snow water equivalent, building confidence in our understanding of conditions in data sparse regions of the world.

A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

National Centers for Environmental Prediction

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Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Garcia, Matthew E.; Mocko, David M.; Tischler, Michael A.; Moran, M. Susan; Thoma, D. P.

2007-01-01

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

NCA-LDAS: An Integrated Terrestrial Water Analysis System for Development, Evaluation, and Dissemination of Climate Indicators

NASA Astrophysics Data System (ADS)

Jasinski, M. F.; Arsenault, K. R.; Beaudoing, H. K.; Bolten, J. D.; Borak, J.; Kumar, S.; Peters-Lidard, C. D.; Li, B.; Liu, Y.; Mocko, D. M.; Rodell, M.

2014-12-01

An Integrated Terrestrial Water Analysis System, or NCA-LDAS, has been created to enable development, evaluation, and dissemination of terrestrial hydrologic climate indicators focusing on the continental U.S. The purpose is to provide quantifiable indicators of states and estimated trends in our nation's water stores and fluxes over a wide range of scales and locations, to support improved understanding and management of water resources and numerous related sectors such as agriculture and energy. NCA-LDAS relies on improved modeling of terrestrial hydrology through assimilation of satellite imagery, building upon the legacy of the Land Information System modeling framework (Kumar et al, 2006; Peters-Lidard et al, 2007). It currently employs the Noah or Catchment Land Surface Model, run with a number of satellite data assimilation scenarios. The domain for NCA-LDAS is the continental U.S. at 1/8 degree grid for the period 1979 to present. Satellite-based variables that are assimilated are soil moisture and snow water equivalent from principally microwave sensors such as SMMR, SSM/I and AMSR, snow covered area from multispectral sensors such as AVHRR, and MODIS, and terrestrial water storage from GRACE. Once simulated, output are evaluated in comparison to independent datasets using a variety of metrics using the Land Surface Verification Toolkit (LVT). LVT schemes within NCA-LDAS also include routines for computing standard statistics of time series such means, max, and linear trends, at various scales. The dissemination of the NCA-LDAS, including model descriptions, forcings, parameters, daily output, indicator results and LVT tools, have been made available to the public through dissemination on NASA GES-DISC.

Simulating the impacts of chronic ozone exposure on plant conductance and photosynthesis, and on the regional hydroclimate using WRF/Chem

NASA Astrophysics Data System (ADS)

Li, Jialun; Mahalov, Alex; Hyde, Peter

2016-11-01

The Noah-Multiparameterization land surface model in the Weather Research and Forecasting (WRF) with Chemistry (WRF/Chem) is modified to include the effects of chronic ozone exposure (COE) on plant conductance and photosynthesis (PCP) found from field experiments. Based on the modified WRF/Chem, the effects of COE on regional hydroclimate have been investigated over the continental United States. Our results indicate that the model with/without modification in its current configuration can reproduce the rainfall and temperature patterns of the observations and reanalysis data, although it underestimates rainfall in the central Great Plains and overestimates it in the eastern coast states. The experimental tests on the effects of COE include setting different thresholds of ambient ozone concentrations ([O3]) and using different linear regressions to quantify PCP against the COE. Compared with the WRF/Chem control run (i.e., without considering the effects of COE), the modified model at different experiment setups improves the simulated estimates of rainfall and temperatures in Texas and regions to the immediate north. The simulations in June, July and August of 2007-2012 show that surface [O3] decrease latent heat fluxes (LH) by 10-27 W m-2, increase surface air temperatures (T 2) by 0.6 °C-2.0 °C, decrease rainfall by 0.9-1.4 mm d-1, and decrease runoff by 0.1-0.17 mm d-1 in Texas and surrounding areas, all of which highly depends on the precise experiment setup, especially the [O3] threshold. The mechanism producing these results is that COE decreases the LH and increases sensible heat fluxes, which in turn increases the Bowen ratios and air temperatures. This lowering of the LH also results in the decrease of convective potential and finally decreases convective rainfall. Employing this modified WRF/Chem model in any high [O3] region can improve the understanding of the interactions of vegetation, meteorology, chemistry/emissions, and crop productivity.

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; White, Kristopher D.

2014-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Global Intercomparison of 12 Land Surface Heat Flux Estimates

NASA Technical Reports Server (NTRS)

Jimenez, C.; Prigent, C.; Mueller, B.; Seneviratne, S. I.; McCabe, M. F.; Wood, E. F.; Rossow, W. B.; Balsamo, G.; Betts, A. K.; Dirmeyer, P. A.;

Inception of the Laurentide Ice Sheet using asynchronous coupling of a regional atmospheric model and an ice model

NASA Astrophysics Data System (ADS)

Birch, L.; Cronin, T.; Tziperman, E.

2017-12-01

The climate over the past 0.8 million years has been dominated by ice ages. Ice sheets have grown about every 100 kyrs, starting from warm interglacials, until they spanned continents. State-of-the-art global climate models (GCMs) have difficulty simulating glacial inception, or the transition of Earth's climate from an interglacial to a glacial state. It has been suggested that this failure may be related to their poorly resolved local mountain topography, due to their coarse spatial resolution. We examine this idea as well as the possible role of ice flow dynamics missing in GCMs. We investigate the growth of the Laurentide Ice Sheet at 115 kya by focusing on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred. We use the Weather Research and Forecasting model (WRF) in a regional, cloud-resolving configuration with resolved mountain terrain to explore how quickly Baffin Island could become glaciated with the favorable yet realizable conditions of 115 kya insolation, cool summers, and wet winters. Using the model-derived mountain glacier mass balance, we force an ice sheet model based on the shallow-ice approximation, capturing the ice flow that may be critical to the spread of ice sheets away from mountain ice caps. The ice sheet model calculates the surface area newly covered by ice and the change in the ice surface elevation, which we then use to run WRF again. Through this type of iterated asynchronous coupling, we investigate how the regional climate responds to both larger areas of ice cover and changes in ice surface elevation. In addition, we use the NOAH-MP Land model to characterize the importance of land processes, like refreezing. We find that initial ice growth on the Penny Ice Cap causes regional cooling that increases the accumulation on the Barnes Ice Cap. We investigate how ice and topography changes on Baffin Island may impact both the regional climate and the large-scale circulation.

Map the Permafrost and its Affected Soils and Vegetation on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhao, L.; Sheng, Y.; Pang, Q.; Zou, D.; Wang, Z.; Li, W.; Wu, X.; Yue, G.; Fang, H.; Zhao, Y.

2015-12-01

Great amount of literatures had been published to deal with the actual distribution and changes of permafrost on the Tibetan Plateau (TP) on the basis of observed ground temperature dataset along Qinghai-Xizang Highway and/or Railway (QXH/R) during the last several decades. But there is very limited data available in the eastern part of the QXH/R and almost no observation in the western part of QXH/R not only for the observed permafrost data, but also for the dataset on ground surface conditions, such as soil and vegetation, which are used as model parameters, initial variables, or benchmark data sets for calibration, validation, and comparison in various Earth System Models (ESMs). To evaluate the status of permafrost and its environmental conditions, such as the distribution and thermal state of permafrost, soil and vegetation on the TP, detailed investigation on permafrost were conducted in 5 regions with different climatic and geologic conditions over the whole plateau from 2009 to 2013, and more than 100 ground temperatures (GTs) monitoring boreholes were drilled and equipped with thermistors, of which 10 sites were equipped with automatic meteorological stations. Geophysical prospecting methods, such as ground penetrating radar (GPR) and electromagnetic prospecting, were used in the same time to detect the permafrost distribution and thicknesses. The monitoring data revealed that the thermal state of permafrost was well correlated with elevation, and regulated by annual precipitation, local geological, geomorphological and hydrological conditions through heat exchanges between ground and atmosphere. Different models, including GTs statistical model, Common Land Surface Model (CoLM), Noah land surface model and TTOP models, were used to map the permafrost in 5 selected regions and the whole TP, while the investigated and monitored data were used as calibration and validation for all models. Finally, we compiled the permafrost map of the TP, soil and vegetation map within the permafrost regions on the TP. We also compiled the soil organic carbon density map of permafrost affected soils on the TP. An overview on permafrost thickness, GTs, ice content was statistically summarized based on investigation data.

Improving Evapotranspiration Estimates Using Multi-Platform Remote Sensing

NASA Astrophysics Data System (ADS)

Knipper, Kyle; Hogue, Terri; Franz, Kristie; Scott, Russell

2016-04-01

Understanding the linkages between energy and water cycles through evapotranspiration (ET) is uniquely challenging given its dependence on a range of climatological parameters and surface/atmospheric heterogeneity. A number of methods have been developed to estimate ET either from primarily remote-sensing observations, in-situ measurements, or a combination of the two. However, the scale of many of these methods may be too large to provide needed information about the spatial and temporal variability of ET that can occur over regions with acute or chronic land cover change and precipitation driven fluxes. The current study aims to improve the spatial and temporal variability of ET utilizing only satellite-based observations by incorporating a potential evapotranspiration (PET) methodology with satellite-based down-scaled soil moisture estimates in southern Arizona, USA. Initially, soil moisture estimates from AMSR2 and SMOS are downscaled to 1km through a triangular relationship between MODIS land surface temperature (MYD11A1), vegetation indices (MOD13Q1/MYD13Q1), and brightness temperature. Downscaled soil moisture values are then used to scale PET to actual ET (AET) at a daily, 1km resolution. Derived AET estimates are compared to observed flux tower estimates, the North American Land Data Assimilation System (NLDAS) model output (i.e. Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model, Mosiac Model, and Noah Model simulations), the Operational Simplified Surface Energy Balance Model (SSEBop), and a calibrated empirical ET model created specifically for the region. Preliminary results indicate a strong increase in correlation when incorporating the downscaling technique to original AMSR2 and SMOS soil moisture values, with the added benefit of being able to decipher small scale heterogeneity in soil moisture (riparian versus desert grassland). AET results show strong correlations with relatively low error and bias when compared to flux tower estimates. In addition, AET results show improved bias to those reported by SSEBop, with similar correlations and errors when compared to the empirical ET model. Spatial patterns of estimated AET display patterns representative of the basin's elevation and vegetation characteristics, with improved spatial resolution and temporal heterogeneity when compared to previous models.

NCEP/NLDAS Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Xia, Y.; Ek, M.; Wood, E.; Luo, L.; Sheffield, J.; Lettenmaier, D.; Livneh, B.; Cosgrove, B.; Mocko, D.; Meng, J.; Wei, H.; Restrepo, P.; Schaake, J.; Mo, K.

2009-05-01

The NCEP Environmental Modeling Center (EMC) collaborated with its CPPA (Climate Prediction Program of the Americas) partners to develop a North American Land Data Assimilation System (NLDAS, http://www.emc.ncep.noaa.gov/mmb/nldas) to monitor and predict the drought over the Continental United States (CONUS). The realtime NLDAS drought monitor, executed daily at NCEP/EMC, including daily, weekly and monthly anomaly and percentile of six fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, precipitation) outputted from four land surface models (Noah, Mosaic, SAC, and VIC) on a common 1/8th degree grid using common hourly land surface forcing. The non-precipitation surface forcing is derived from NCEP's retrospective and realtime North American Regional Reanalysis System (NARR). The precipitation forcing is anchored to a daily gauge-only precipitation analysis over CONUS that applies a Parameter-elevation Regressions on Independent Slopes Model (PRISM) correction. This daily precipitation analysis is then temporally disaggregated to hourly precipitation amounts using radar and satellite precipitation. The NARR- based surface downward solar radiation is bias-corrected using seven years (1997-2004) of GOES satellite- derived solar radiation retrievals. The uncoupled ensemble seasonal drought prediction utilizes the following three independent approaches for generating downscaled ensemble seasonal forecasts of surface forcing: (1) Ensemble Streamflow Prediction, (2) CPC Official Seasonal Climate Outlook, and (3) NCEP CFS ensemble dynamical model prediction. For each of these three approaches, twenty ensemble members of forcing realizations are generated using a Bayesian merging algorithm developed by Princeton University. The three forcing methods are then used to drive the VIC model in seasonal prediction mode over thirteen large river basins that together span the CONUS domain. One to nine month ensemble seasonal prediction products such as air temperature, precipitation, soil moisture, snowpack, total runoff, evaporation and streamflow are derived for each forcing approach. The anomalies and percentiles of the predicted products for each approach may be used for CONUS drought prediction. This system is executed at the beginning of each month and distributes its products by the 10th of each month. The prediction products are evaluated using corresponding monitoring products for the VIC model and are compared with the prediction products from other research groups (e.g., University of Washington at Seattle, NASA Goddard) in the CONUS.

Disseminating near-real-time hazards information and flood maps in the Philippines through Web-GIS.

PubMed

A Lagmay, Alfredo Mahar Francisco; Racoma, Bernard Alan; Aracan, Ken Adrian; Alconis-Ayco, Jenalyn; Saddi, Ivan Lester

2017-09-01

The Philippines being a locus of tropical cyclones, tsunamis, earthquakes and volcanic eruptions, is a hotbed of disasters. These natural hazards inflict loss of lives and costly damage to property. Situated in a region where climate and geophysical tempest is common, the Philippines will inevitably suffer from calamities similar to those experienced recently. With continued development and population growth in hazard prone areas, it is expected that damage to infrastructure and human losses would persist and even rise unless appropriate measures are immediately implemented by government. In 2012, the Philippines launched a responsive program for disaster prevention and mitigation called the Nationwide Operational Assessment of Hazards (Project NOAH), specifically for government warning agencies to be able to provide a 6hr lead-time warning to vulnerable communities against impending floods and to use advanced technology to enhance current geo-hazard vulnerability maps. To disseminate such critical information to as wide an audience as possible, a Web-GIS using mashups of freely available source codes and application program interface (APIs) was developed and can be found in the URLs http://noah.dost.gov.ph and http://noah.up.edu.ph/. This Web-GIS tool is now heavily used by local government units in the Philippines in their disaster prevention and mitigation efforts and can be replicated in countries that have a proactive approach to address the impacts of natural hazards but lack sufficient funds. Copyright © 2017. Published by Elsevier B.V.

Elemental profiling of Noah's Ark shell (Arca noae, Linnaeus, 1758) by plasma optical spectrometry and chemometric tools.

PubMed

Kobelja, Kristina; Nemet, Ivan; Župan, Ivan; Čulin, Jelena; Rončević, Sanda

2016-12-01

Determination of metal content in biominerals provides essential information with respect to relations between biomineralization processes and environmental status. Mussels are species that have a great potential as bio-marker species and therefore, they are in the focus of numerous biomineralization and ecological studies. In this study, elemental profile of mussel shell of Noah's Ark (Arca noe, Linnaeus, 1758), which inhabit eastern Adriatic Sea was obtained by determination of seventeen elements content using inductively coupled plasma optical emission spectrometry (ICP-OES). Shell samples were collected from marine protected area and from marine shipping route in eastern Adriatic Sea. The accuracy of applied analytical procedure based on microwave decomposition of shell samples was tested by use of reference materials of limestone and by matrix-matched standards. By aid of chemometric methods, the elemental profile along with variability of elements content of shell was obtained. The impact of different environment on elements content was established by use of multivariate statistical PCA method. Discernment between two groups of samples was manifested. Among results of main, minor and trace elements content, the last one which denoted to Cd, Co, Cu, Pb, and Mn was expressed as principal distinctive feature of shell samples collected from different sampling sites. Elemental profiling of mussel shell Noah's Ark provides novel insight in species status as well as in environmental status on the observed locations. Copyright © 2016 Elsevier GmbH. All rights reserved.

Understanding Drought and Regional Conservation Efforts on Urban Ecohydrology in Southern California

NASA Astrophysics Data System (ADS)

Hogue, T. S.

2015-12-01

Cities in the western U.S. are under increasing pressure to reduce the demand of imported water through increasing conservation efforts, altering non-native landscapes, and enhancing local water supplies. The State of California adopted emergency regulations implementing a mandatory 25% statewide reduction in potable urban water use and agricultural restrictions have also been enacted. The complexities in urban water flows and lack of granular data make understanding the impact of conservation and demand change on regional ecohydrology difficult. This presentation highlights ongoing work to better understand the coupling between humans, water and ecosystems in semi-arid urban cities, using metropolitan southern California as a case study. We evaluate historical and contemporary ecohydrologic behavior and human impacts through intensive data collection, remote sensing and high resolution modeling. The change in outdoor irrigation rates due to recent conservation measures (2008-2010) has resulted in overall decreased greenness and reduced dry season streamflow; however significant variability in conservation response is observed. Groundwater recharge, artificially supported by landscape irrigation, is also being impacted. In general, anthropogenic water fluxes (irrigation, pipe leakage, spreading grounds) are not parameterized in hydrologic and land surface models applied over urban areas. Inclusion of landscape irrigation significantly improves neighborhood scale simulations of evaporative fluxes and land surface temperatures and results in shifts in the energy partitioning. The cooling effects of irrigation on daily air temperatures has the largest influence over low intensity residential areas, with an average 2°C decrease observed in coupled model simulations (WRF-Noah-UCM). Ultimately, we strive to improve predictions of human-water interactions in semi-arid cities to better understand the effectiveness and impacts of ongoing drought and conservation efforts and guide demand strategies under future climate variability.

Medieval Theatre: It's More Fun than It Looks.

ERIC Educational Resources Information Center

Fitzhugh, Mike

1996-01-01

Explores production ideas for plays other than works by Shakespeare, including medieval plays such as the "Wakefield Noah" by the Wakefield Master. Lists some questions to consider when deciding to perform a medieval play. (PA)

Numerical Modelling of Freshwater Inputs in the Shelf Area of the Ofanto River (Southern Italy)

NASA Astrophysics Data System (ADS)

Verri, G.; Pinardi, N.; Tribbia, J. J.; Gochis, D.; Bryan, F.; Tseng, Y. H.; Navarra, A.; Coppini, G.

2016-02-01

The aim of this study is to understand and to assess the effects of river freshwater release on the ocean circulation and dynamics focusing on the shelf area near estuaries. A sensitivity study to different modelling approaches, which point to the representation of the dynamics of the river inflow, are presented. The modeling strategy we chose consists of an integrated modeling chain including the atmosphere, the hydrology/hydraulics and the estuarine dynamics in order to force our regional ocean model at the Ofanto outlet in a reliable way. This meteo-hydrological modeling chain allows us to take into account all the physical processes involved in the local water cycle of the Ofanto catchment such as the rainfall, the land surface infiltration/evaporation, the partitioning of total runoff into surface and subsurface runoff and the channel streamflow. In order to achieve our goal, we chose the Ofanto river catchment and its estuary as case study. The Ofanto river is a torrential river flowing across the Southern Italy and ending in the Adriatic Sea; its annual averaged discharge is low (15 m3s-1 following Raicich, 1996) but may significantly increase when heavy rain events occur. In details our regional ocean model is a finite difference numerical model based on NEMO code (Madec, G., 2008) and implemented in the Central Mediterranean Sea with 2km as horizontal resolution. The meteo-hydrological modeling chain consists of: 1) the WRF-ARW model (Skamarock et al., 2008) including NOAH-MP as Land Surface Submodel,; 2) WRF-HYDRO model (Gochis D., et al., 2013) representing the hydrology/hydraulics component with 200m as horizontal resolution, simulating the streamflow discharge along the Ofanto river network.; 3) finally an estuarine box model (Garvine et al., 2006) is inserted downstream of WRF-Hydro and upstream of the regional ocean model. A set of sensitivity experiments has been performed aiming to evaluate the capability of the regional ocean model to decribe the Ofanto river plume by providing hindcast discharge and salinity from the estuary model at the river mouth with different methods. The time window of the simulations covers the first three months of year 2011, since 4 heavy rain events affected the Ofanto catchment in this period.

Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

2017-12-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts. These combined satellite and model records and forecasts are intended for use in different decision support tools, like the Famine Early Warning Systems Network (FEWS NET) and the Middle East-North Africa (MENA) Regional Drought Management System, for aiding and forecasting in water and food insecure regions.

Revisiting the PLUMBER Experiments from a Process-Diagnostics Perspective

NASA Astrophysics Data System (ADS)

Nearing, G. S.; Ruddell, B. L.; Clark, M. P.; Nijssen, B.; Peters-Lidard, C. D.

2017-12-01

The PLUMBER benchmarking experiments [1] showed that some of the most sophisticated land models (CABLE, CH-TESSEL, COLA-SSiB, ISBA-SURFEX, JULES, Mosaic, Noah, ORCHIDEE) were outperformed - in simulations of half-hourly surface energy fluxes - by instantaneous, out-of-sample, and globally-stationary regressions with no state memory. One criticism of PLUMBER is that the benchmarking methodology was not derived formally, so that applying a similar methodology with different performance metrics can result in qualitatively different results. Another common criticism of model intercomparison projects in general is that they offer little insight into process-level deficiencies in the models, and therefore are of marginal value for helping to improve the models. We address both of these issues by proposing a formal benchmarking methodology that also yields a formal and quantitative method for process-level diagnostics. We apply this to the PLUMBER experiments to show that (1) the PLUMBER conclusions were generally correct - the models use only a fraction of the information available to them from met forcing data (<50% by our analysis), and (2) all of the land models investigated by PLUMBER have similar process-level error structures, and therefore together do not represent a meaningful sample of structural or epistemic uncertainty. We conclude by suggesting two ways to improve the experimental design of model intercomparison and/or model benchmarking studies like PLUMBER. First, PLUMBER did not report model parameter values, and it is necessary to know these values to separate parameter uncertainty from structural uncertainty. This is a first order requirement if we want to use intercomparison studies to provide feedback to model development. Second, technical documentation of land models is inadequate. Future model intercomparison projects should begin with a collaborative effort by model developers to document specific differences between model structures. This could be done in a reproducible way using a unified, process-flexible system like SUMMA [2]. [1] Best, M.J. et al. (2015) 'The plumbing of land surface models: benchmarking model performance', J. Hydrometeor. [2] Clark, M.P. et al. (2015) 'A unified approach for process-based hydrologic modeling: 1. Modeling concept', Water Resour. Res.

Reconstruction of droughts in India using multiple land-surface models (1951-2015)

NASA Astrophysics Data System (ADS)

Mishra, Vimal; Shah, Reepal; Azhar, Syed; Shah, Harsh; Modi, Parth; Kumar, Rohini

2018-04-01

India has witnessed some of the most severe historical droughts in the current decade, and severity, frequency, and areal extent of droughts have been increasing. As a large part of the population of India is dependent on agriculture, soil moisture drought affecting agricultural activities (crop yields) has significant impacts on socio-economic conditions. Due to limited observations, soil moisture is generally simulated using land-surface hydrological models (LSMs); however, these LSM outputs have uncertainty due to many factors, including errors in forcing data and model parameterization. Here we reconstruct agricultural drought events over India during the period of 1951-2015 based on simulated soil moisture from three LSMs, the Variable Infiltration Capacity (VIC), the Noah, and the Community Land Model (CLM). Based on simulations from the three LSMs, we find that major drought events occurred in 1987, 2002, and 2015 during the monsoon season (June through September). During the Rabi season (November through February), major soil moisture droughts occurred in 1966, 1973, 2001, and 2003. Soil moisture droughts estimated from the three LSMs are comparable in terms of their spatial coverage; however, differences are found in drought severity. Moreover, we find a higher uncertainty in simulated drought characteristics over a large part of India during the major crop-growing season (Rabi season, November to February: NDJF) compared to those of the monsoon season (June to September: JJAS). Furthermore, uncertainty in drought estimates is higher for severe and localized droughts. Higher uncertainty in the soil moisture droughts is largely due to the difference in model parameterizations (especially soil depth), resulting in different persistence of soil moisture simulated by the three LSMs. Our study highlights the importance of accounting for the LSMs' uncertainty and consideration of the multi-model ensemble system for the real-time monitoring and prediction of drought over India.

Noah Porter's problem and the origins of American psychology.

PubMed

Richards, Graham

2004-01-01

The twin problems facing nineteenth-century American "mental and moral philosophy" of the nature of psychological language and the constraints that religious beliefs placed on possibilities of innovation in a "scientific Psychology" are both highly visible in the work of Noah Porter, who was unable to resolve them. They are also more covertly identifiable in the works of James McCosh and others in this school. It is suggested that the transition to the "New Psychology" of the 1880s and 1890s needs to be rethought in light of this in three respects: (a) ironically, it entailed repressing insights into the psychological language problem, (b) the legacy of the religious factor profoundly affected U.S. Psychology and played a less unambiguously negative role in its fortunes than customarily portrayed, and (c) the transition was itself a more complex and protracted process than is portrayed in traditional "revolutionary" accounts. Copyright 2004 Wiley Periodicals, Inc.

Correction

NASA Astrophysics Data System (ADS)

2014-09-01

An error was made in the spelling of the name of Noah Petro, who was quoted in the news article "The summer of supermoons," published in the 19 August 2014 issue of Eos (95(33), 297, doi:10.1002/2014EO330005). Eos regrets the error.

Operational and LIS-Based North American Land Data Assimilation Systems at National Centers for Environmental Prediction: Capability in Simulating Water and Energy Budget over the Western United States

NASA Astrophysics Data System (ADS)

Mitchell, K.; Xia, Y.; Ek, M. B.; Mocko, D. M.; Kumar, S.; Peters-Lidard, C. D.

2016-12-01

NLDAS is a multi-institutional collaborative project sponsored by NOAA's Climate Program Office and NASA's Terrestrial Hydrological Program. NLDAS has a long successful history of producing soil moisture, snow cover, total runoff and streamflow products via application of surface meteorology and precipitation datasets to drive four land-surface models (i.e., Noah, Mosaic, SAC, VIC). The purpose of the NLDAS system is to support numerous research and operational applications in the land modeling and water resources management communities. Since the operational NLDAS version was successfully implemented at NCEP in August 2014, NLDAS products are being used by over 5000 users annually worldwide, including academia, governmental agencies, and private enterprises. Over 71 million files and 144 Tb of data were downloaded in 2015. As we endeavor to increase the quality and breadth of NLDAS products, a joint effort between NASA and NCEP is underway to enable the assimilation of hydrology-relevant remote sensing datasets within NLDAS through the NASA Land Information System (LIS). The use of LIS will also enable easier transition of newly upgraded land surface models into NCEP NLDAS operations. Cold season processes significantly affect water and energy cycles, and their partitioning. As such, in the evaluation of NLDAS systems it is important to assess water and energy exchanges and/or partitioning processes over high-elevations. The Rocky Mountain region of the western U. S. is chosen as such a region to analyze and compare snow water equivalent (SWE), snow cover, snow melt, snow sublimation, total runoff, and sensible heat and latent heat flux. Reference data sets (observation-based and reanalysis) of monthly SWE, streamflow, evapotranspiration, GRACE-based total water storage change, and energy fluxes are used to evaluate model-simulated results. The results show several key factors that affect model simulations: (1) forcing errors such as precipitation partitioning into snowfall and rainfall, (2) snow albedo, (3) refreezing of melted snow, (4) boundary layer stability, and (5) freezing and thawing of soil. Though the anomaly correlations indicate good agreement with the observations or reanalysis products, large quantitative differences are evident in certain cases.

Bunched black (and grouped grey) swans: Dissipative and non-dissipative models of correlated extreme fluctuations in complex geosystems

NASA Astrophysics Data System (ADS)

Watkins, N. W.

2013-01-01

I review the hierarchy of approaches to complex systems, focusing particularly on stochastic equations. I discuss how the main models advocated by the late Benoit Mandelbrot fit into this classification, and how they continue to contribute to cross-disciplinary approaches to the increasingly important problems of correlated extreme events and unresolved scales. The ideas have broad importance, with applications ranging across science areas as diverse as the heavy tailed distributions of intense rainfall in hydrology, after which Mandelbrot named the "Noah effect"; the problem of correlated runs of dry summers in climate, after which the "Joseph effect" was named; and the intermittent, bursty, volatility seen in finance and fluid turbulence.

Optimization of canopy conductance models from concurrent measurements of sap flow and stem water potential on Drooping Sheoak in South Australia

NASA Astrophysics Data System (ADS)

Wang, H.; Guan, H.; Deng, R.; Simmons, C. T.

2013-12-01

Canopy conductance response to environmental conditions is a critical component in land surface hydrological modeling. This response is often formulated as a combination of response functions of each influencing factor (solar radiation, air temperature, vapor pressure deficit, and soil water availability). These functions are climate and vegetation specific. Thus, it is important to determine the most appropriate combination of response functions and their parameter values for a specific environment. We will present a method for this purpose based on field measurements and an optimization scheme. The study was performed on Drooping Sheoak (Allocasuarina verticillata) in Adelaide South Australia. Sap flow and stem water potential were measured in a year together with microclimate variables. Canopy conductance was calculated from the inversed Penman-Monteith (PM) equation, which was then used to examine the performance of 36 combinations of various response functions. Parameters in the models were optimized using a DiffeRential Evolution Adaptive Metropolis (DREAM) model based on a training dataset. The testing results show that the best combination gave a correlation coefficient of 0.97, and root mean square error of 0.0006 m/s in comparison to the PM-calculated values. The maximum stomatal conductance given by this combination is 0.0075 m/s, equivalent to a minimum stomatal resistance of 133 s/m. This is close to the number (150 s/m) used in Noah land surface model for evergreen needle-leaf trees. It is surprising that for all combinations, the optimized parameter of the temperature response function is against its physical meaning. This is likely related to the inter-dependence between air temperature and vapor pressure deficit. Supported by the results, we suggest that the effects of vapor pressure deficit and air temperature should be represented together, so as to be consistent with the physics.

Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

USGS Publications Warehouse

Romaguera, Mireia; Vaughan, R. Greg; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F.D.

2018-01-01

This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of LST, the LSTgt. We hypothesize that in geothermal areas the LSM time series will underestimate the LST as compared to the remote sensing data, since the former does not account for the geothermal component in its model.In order to extract LSTgt, two approaches of different nature (physical based and data mining) were developed and tested in an area of about 560 × 560 km2 centered at the Kenyan Rift. Pre-dawn data in the study area during the first 45 days of 2012 were analyzed.The results show consistent spatial and temporal LSTgt patterns between the two approaches, and systematic differences of about 2 K. A geothermal area map from surface studies was used to assess LSTgt inside and outside the geothermal boundaries. Spatial means were found to be higher inside the geothermal limits, as well as the relative frequency of occurrence of high LSTgt. Results further show that areas with strong topography can result in anomalously high LSTgt values (false positives), which suggests the need for a slope and aspect correction in the inputs to achieve realistic results in those areas. The uncertainty analysis indicates that large uncertainties of the input parameters may limit detection of LSTgt anomalies. To validate the approaches, higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over the Olkaria geothermal field were used. An established method to estimate radiant geothermal flux was applied providing values between 9 and 24 W/m2 in the geothermal area, which coincides with the LSTgt flux rates obtained with the proposed approaches.The proposed approaches are a first step in estimating LSTgt at large spatial coverage from remote sensing and LSM data series, and provide an innovative framework for future improvements.

ADHydro: A Parallel Implementation of a Large-scale High-Resolution Multi-Physics Distributed Water Resources Model Using the Charm++ Run Time System

NASA Astrophysics Data System (ADS)

Steinke, R. C.; Ogden, F. L.; Lai, W.; Moreno, H. A.; Pureza, L. G.

2014-12-01

Physics-based watershed models are useful tools for hydrologic studies, water resources management and economic analyses in the contexts of climate, land-use, and water-use changes. This poster presents a parallel implementation of a quasi 3-dimensional, physics-based, high-resolution, distributed water resources model suitable for simulating large watersheds in a massively parallel computing environment. Developing this model is one of the objectives of the NSF EPSCoR RII Track II CI-WATER project, which is joint between Wyoming and Utah EPSCoR jurisdictions. The model, which we call ADHydro, is aimed at simulating important processes in the Rocky Mountain west, including: rainfall and infiltration, snowfall and snowmelt in complex terrain, vegetation and evapotranspiration, soil heat flux and freezing, overland flow, channel flow, groundwater flow, water management and irrigation. Model forcing is provided by the Weather Research and Forecasting (WRF) model, and ADHydro is coupled with the NOAH-MP land-surface scheme for calculating fluxes between the land and atmosphere. The ADHydro implementation uses the Charm++ parallel run time system. Charm++ is based on location transparent message passing between migrateable C++ objects. Each object represents an entity in the model such as a mesh element. These objects can be migrated between processors or serialized to disk allowing the Charm++ system to automatically provide capabilities such as load balancing and checkpointing. Objects interact with each other by passing messages that the Charm++ system routes to the correct destination object regardless of its current location. This poster discusses the algorithms, communication patterns, and caching strategies used to implement ADHydro with Charm++. The ADHydro model code will be released to the hydrologic community in late 2014.

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

NASA Astrophysics Data System (ADS)

Verri, Giorgia; Pinardi, Nadia; Gochis, David; Tribbia, Joseph; Navarra, Antonio; Coppini, Giovanni; Vukicevic, Tomislava

2017-10-01

A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology-hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph.

Dismantling Noah's Ark.

ERIC Educational Resources Information Center

Lorber, Judith

1986-01-01

Presents a prescription for a restructured postindustrial society without gender as an organizing principle. The potential nongendered social order is described in terms of nongendered reproduction, equally valued wage work and a gender-neutral wage structure, and gender-neutral access to authority and power. (SA)

[Applicability of established drought index in Huang-Huai-Hai region based on actual evapotranspiration.

PubMed

Wang, Ying; Wu, Rong Jun; Guo, Zhao Bing

2016-05-01

Based on the modeled products of actual evapotranspiration with NOAH land surface model, the temporal and spatial variations of actual evapotranspiration were analyzed for the Huang-Huai-Hai region in 2002-2010. In the meantime, the agricultural drought index, namely, drought severity index (DSI) was constructed, incorporated with products of MOD17 potential evapotranspiration and MOD13 NDVI. Furthermore, the applicability of established DSI in this region in the whole year of 2002 was investigated based on the Palmer drought severity index (PDSI), the yield reduction rate of winter wheat, and drought severity data. The results showed that the annual average actual evapotranspiration within the survey region increased from the northwest to the southeast, with the maximum of 800-900 mm in the southeast and the minimum less than 300 mm in the northwest. The DSI and PDSI had positive correlation (R 2 =0.61) and high concordance in change trend. They all got the low point (-0.61 and -1.33) in 2002 and reached the peak (0.81 and 0.92) in 2003. The correlation between DSI and yield reduction rate of winter wheat (R 2 =0.43) was more significant than that between PDSI and yield reduction rate of winter wheat (R 2 =0.06). So, the DSI reflected a high spatial resolution of drought pattern and could reflect the region agricultural drought severity and intensity more accurately.

Faith in floods: Field and theory in landscape evolution before geomorphology

NASA Astrophysics Data System (ADS)

Montgomery, David R.

2013-10-01

Opinions about the origin of topography have long marked the frontier between science and religion. The creation of the world we know is central to religious and secular world views; and until recently the power to shape landscapes lay beyond the reach of mortals, inviting speculation as to a role for divine intervention. For centuries, Christians framed rational inquiry into the origin of topography around theories for how Noah's Flood shaped mountains and carved valleys. Only as geologists learned how to decipher Earth history and read the signature of Earth surface processes did naturalists come to understand the forces that shaped the world. In this sense, the historical roots of geomorphology lie in the tension between faith in theories and the compelling power of field observations—issues that remain relevant to the practice of geomorphology today.

Information-Theoretic Benchmarking of Land Surface Models

NASA Astrophysics Data System (ADS)

Nearing, Grey; Mocko, David; Kumar, Sujay; Peters-Lidard, Christa; Xia, Youlong

2016-04-01

Benchmarking is a type of model evaluation that compares model performance against a baseline metric that is derived, typically, from a different existing model. Statistical benchmarking was used to qualitatively show that land surface models do not fully utilize information in boundary conditions [1] several years before Gong et al [2] discovered the particular type of benchmark that makes it possible to *quantify* the amount of information lost by an incorrect or imperfect model structure. This theoretical development laid the foundation for a formal theory of model benchmarking [3]. We here extend that theory to separate uncertainty contributions from the three major components of dynamical systems models [4]: model structures, model parameters, and boundary conditions describe time-dependent details of each prediction scenario. The key to this new development is the use of large-sample [5] data sets that span multiple soil types, climates, and biomes, which allows us to segregate uncertainty due to parameters from the two other sources. The benefit of this approach for uncertainty quantification and segregation is that it does not rely on Bayesian priors (although it is strictly coherent with Bayes' theorem and with probability theory), and therefore the partitioning of uncertainty into different components is *not* dependent on any a priori assumptions. We apply this methodology to assess the information use efficiency of the four land surface models that comprise the North American Land Data Assimilation System (Noah, Mosaic, SAC-SMA, and VIC). Specifically, we looked at the ability of these models to estimate soil moisture and latent heat fluxes. We found that in the case of soil moisture, about 25% of net information loss was from boundary conditions, around 45% was from model parameters, and 30-40% was from the model structures. In the case of latent heat flux, boundary conditions contributed about 50% of net uncertainty, and model structures contributed about 40%. There was relatively little difference between the different models. 1. G. Abramowitz, R. Leuning, M. Clark, A. Pitman, Evaluating the performance of land surface models. Journal of Climate 21, (2008). 2. W. Gong, H. V. Gupta, D. Yang, K. Sricharan, A. O. Hero, Estimating Epistemic & Aleatory Uncertainties During Hydrologic Modeling: An Information Theoretic Approach. Water Resources Research 49, 2253-2273 (2013). 3. G. S. Nearing, H. V. Gupta, The quantity and quality of information in hydrologic models. Water Resources Research 51, 524-538 (2015). 4. H. V. Gupta, G. S. Nearing, Using models and data to learn: A systems theoretic perspective on the future of hydrological science. Water Resources Research 50(6), 5351-5359 (2014). 5. H. V. Gupta et al., Large-sample hydrology: a need to balance depth with breadth. Hydrology and Earth System Sciences Discussions 10, 9147-9189 (2013).

Law suit over evidence for Noah's flood

NASA Astrophysics Data System (ADS)

Gwynne, Peter

2017-07-01

An Australian-born geologist is suing the United States National Parks Service over its refusal to allow him to remove about 60 rocks - each weighing around 250 g - from the banks of the Colorado River, which flows through the Grand Canyon in Arizona.

Redefining Democracy for the Modern State.

ERIC Educational Resources Information Center

Rahe, Paul A.

1992-01-01

Draws distinctions between classical and modern concepts of democracy. Contrasts Pythagoras' dislike of factions with Madison's support for economic differentiation and religious toleration. Discusses Aristotle's and Noah Webster's ideas on addressing class tensions. Examines early U.S. theorists' suspicions of direct democracy and support for…

Early Adolescence.

ERIC Educational Resources Information Center

Cronin, Linda L.; Padilla, Michael J.

1984-01-01

Describes science activities related to endangered species designed to sensitize students to the process of extinction; learn of the human role in that process; and emphasize the importance of National Wildlife Week. Provides activities and games such as drift traps, webbing, making corrections, What animal am I?, and Noah's Ark. (JM)

Children as Illustrators: A Transcultural Experience.

ERIC Educational Resources Information Center

Hurwitz, Al

1980-01-01

The author discusses his cross cultural study of the painting styles of 9- to 12-year-old children in Australia, New Zealand, and South Korea. He compares their art products--all illustrations of the Noah's Ark story. A sample of the drawings illustrates the text. (SJL)

Spectroscopic Studies of Melanin.

DTIC Science & Technology

1986-01-01

operation of the laser optics; Mr. Thomas Haw; Dr. James Gallas; Ms. Christine L. Noah- Cooper for stimulating and useful conversations; and Lottie B...168B. 14. Kozikowski SD, Wolfram LJ, Alfano RR. Fluorescence spectroscopy of eumelanins. IEEE J Quant Electron 1984;OE20:1379-1382. 15. Slawinski J

Developing and Applying a Multi-scale Framework to Study the Relationship between Landscapes and Coastal Waters in the Texas Gulf Coast in a Changing Climate

NASA Astrophysics Data System (ADS)

Yang, Z. L.; McClelland, J. W.; Su, H.; Cai, X.; Lin, P.; Tavakoly, A. A.; Griffin, C. G.; Turner, E.; Maidment, D. R.; Montagna, P.

2014-12-01

This study seeks to improve our understanding of how upland landscapes and coastal waters, which are connected by watersheds, respond to changes in hydrological and biogeochemical cycles resulting from changes in climate, local weather patterns, and land use. This paper will report our progress in the following areas. (1) The Noah-MP land surface model is augmented to include the soil nitrogen leaching and plants fixation and uptake of nitrogen. (2) We have evaluated temperature, precipitation and runoff change (2039-2048 relative to 1989-1998) patterns in Texas under the A2 emission scenario using the North American Regional Climate Change Assessment Program (NARCCAP) product. (3) We have linked a GIS-based river routing model (RAPID) and a GIS-based nitrogen input dataset (TX-ANB). The modeling framework was conducted for total nitrogen (TN) load estimation in the San Antonio and Guadalupe basins. (4) Beginning in July 2011, the Colorado, Guadalupe, San Antonio, and Nueces rivers have been sampled on a monthly basis. Sampling continued until November 2013. We also have established an on-going citizen science sampling program. We have contacted the Lower Colorado River Authority and the Texas Stream Team at Texas State University to solicit participation in our program. (5) We have tested multiple scenarios of nutrient contribution to South Texas bays. We are modeling the behavior of these systems under stress due to climate change such as less overall freshwater inflow, increased inorganic nutrient loading, and more frequent large storms.

Round Robin evaluation of soil moisture retrieval models for the MetOp-A ASCAT Instrument

NASA Astrophysics Data System (ADS)

Gruber, Alexander; Paloscia, Simonetta; Santi, Emanuele; Notarnicola, Claudia; Pasolli, Luca; Smolander, Tuomo; Pulliainen, Jouni; Mittelbach, Heidi; Dorigo, Wouter; Wagner, Wolfgang

2014-05-01

Global soil moisture observations are crucial to understand hydrologic processes, earth-atmosphere interactions and climate variability. ESA's Climate Change Initiative (CCI) project aims to create a global consistent long-term soil moisture data set based on the merging of the best available active and passive satellite-based microwave sensors and retrieval algorithms. Within the CCI, a Round Robin evaluation of existing retrieval algorithms for both active and passive instruments was carried out. In this study we present the comparison of five different retrieval algorithms covering three different modelling principles applied to active MetOp-A ASCAT L1 backscatter data. These models include statistical models (Bayesian Regression and Support Vector Regression, provided by the Institute for Applied Remote Sensing, Eurac Research Viale Druso, Italy, and an Artificial Neural Network, provided by the Institute of Applied Physics, CNR-IFAC, Italy), a semi-empirical model (provided by the Finnish Meteorological Institute), and a change detection model (provided by the Vienna University of Technology). The algorithms were applied on L1 backscatter data within the period of 2007-2011, resampled to a 12.5 km grid. The evaluation was performed over 75 globally distributed, quality controlled in situ stations drawn from the International Soil Moisture Network (ISMN) using surface soil moisture data from the Global Land Data Assimilation System (GLDAS-) Noah land surface model as second independent reference. The temporal correlation between the data sets was analyzed and random errors of the the different algorithms were estimated using the triple collocation method. Absolute soil moisture values as well as soil moisture anomalies were considered including both long-term anomalies from the mean seasonal cycle and short-term anomalies from a five weeks moving average window. Results show a very high agreement between all five algorithms for most stations. A slight vegetation dependency of the errors and a spatial decorrelation of the performance patterns of the different algorithms was found. We conclude that future research should focus on understanding, combining and exploiting the advantages of all available modelling approaches rather than trying to optimize one approach to fit every possible condition.

Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

2016-04-01

Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., Al-Shrafany, D., Islam, T., 2013b. Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model. Water Resources Management 27, 5069-5087. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., O'Neill, P., Islam, T., Gupta, M., 2014. Assessment of SMOS soil moisture retrieval parameters using tau-omega algorithms for soil moisture deficit estimation. Journal of Hydrology 519, 574-587.

Noah and EVE (Environmental Values Education).

ERIC Educational Resources Information Center

Knapp, Clifford

1995-01-01

Environmental ethics provide a set of related values that help to limit or restrict individual freedom in order to save and protect nature. Examples of environmental ethics include land ethics, deep ecology, social ecology, Native or first peoples' worldviews, reverence for life, and conservation and management. Includes teaching strategies and a…

Runaways.

ERIC Educational Resources Information Center

Greenberg, Keith Elliot

This essay with photographs describes the experiences of two runaways, examining why they left home and how they found help. Although runaways have a reputation for being irresponsible, they usually have good reasons for leaving home. The nun who ran Noah's Ark, where both the runaways featured found shelter and help, estimated that only about two…

Melanin: The Effects of Dimethyl Sulfoxide on the Spectral Properties.

DTIC Science & Technology

1986-01-01

the interpretation of the spectral data; Ms. Christine L. Noah-Cooper for stimulating and useful discussions; ’s. Lottie R. Applewhite for editorial...Photobiol 1978;28:75-81. 13. Gallas JP. Fluorescence of melanin. Dtiss Abstr Int 1982;43:1681. 14. Kozikowski SD, Wolfram LJ, Alfano RR. Fluorescence

Islam Does Not Inhibit Science.

ERIC Educational Resources Information Center

Shanavas, T. O.

1999-01-01

Compares the science/religion relationship in both Christian and Islamic countries. Presents Muslim scholars' ideas about the presence of humans on earth. Presents ideas on active nature, Noah's curse, and the age of the universe. Refutes the notion that Islam inhibited science and advocates the belief that Islam promoted science. (YDS)

Dictionaries: British and American. The Language Library.

ERIC Educational Resources Information Center

Hulbert, James Root

An account of the dictionaries, great and small, of the English-speaking world is given in this book. Subjects covered include the origin of English dictionaries, early dictionaries, Noah Webster and his successors to the present, abridged dictionaries, "The Oxford English Dictionary" and later dictionaries patterned after it, the…

Multiple-resolution Modeling of flood processes in urban catchments using WRF-Hydro: A Case Study in south Louisiana.

NASA Astrophysics Data System (ADS)

Saad, H.; Habib, E. H.

2017-12-01

In August 2016, the city of Lafayette and many other urban centers in south Louisiana experienced catastrophic flooding resulting from prolonged rainfall. Statewide, this historic storm displaced more than 30,000 people from their homes, resulted in damages up to $8.7 billion, put rescue workers at risk, interrupted institutions of education and business, and worst of all, resulted in the loss of life of at least 13 Louisiana residents. With growing population and increasing signs of climate change, the frequency of major floods and severe storms is expected to increase, as will the impacts of these events on our communities. Local communities need improved capabilities for forecasting flood events, monitoring of flood impacts on roads and key infrastructure, and effectively communicating real-time flood dangers at scales that are useful to the public. The current study presents the application of the WRF-Hydro modeling system to represent integrated hydrologic, hydraulic and hydrometeorological processes that drive flooding in urban basins at temporal and spatial scales that can be useful to local communities. The study site is the 25- mile2 Coulee mine catchment in Lafayette, south Louisiana. The catchment includes two tributaries with natural streams located within mostly agricultural lands. The catchment crosses the I-10 highway and through the metropolitan area of the City of Lafayette into a man-made channel, which eventually drains into the Vermilion River and the Gulf of Mexico. Due to its hydrogeomorphic setting, local and rapid diversification of land uses, low elevation, and interdependent infrastructure, the integrated modeling of this coulee is considered a challenge. A nested multi-scale model is being built using the WRF-HYDRO, with 500m and 10m resolutions for the NOAH land-surface model and diffusive wave terrain routing grids, respectively.

ADHydro: A Large-scale High Resolution Multi-Physics Distributed Water Resources Model for Water Resource Simulations in a Parallel Computing Environment

NASA Astrophysics Data System (ADS)

lai, W.; Steinke, R. C.; Ogden, F. L.

2013-12-01

Physics-based watershed models are useful tools for hydrologic studies, water resources management and economic analyses in the contexts of climate, land-use, and water-use changes. This poster presents development of a physics-based, high-resolution, distributed water resources model suitable for simulating large watersheds in a massively parallel computing environment. Developing this model is one of the objectives of the NSF EPSCoR RII Track II CI-WATER project, which is joint between Wyoming and Utah. The model, which we call ADHydro, is aimed at simulating important processes in the Rocky Mountain west, includes: rainfall and infiltration, snowfall and snowmelt in complex terrain, vegetation and evapotranspiration, soil heat flux and freezing, overland flow, channel flow, groundwater flow and water management. The ADHydro model uses the explicit finite volume method to solve PDEs for 2D overland flow, 2D saturated groundwater flow coupled to 1D channel flow. The model has a quasi-3D formulation that couples 2D overland flow and 2D saturated groundwater flow using the 1D Talbot-Ogden finite water-content infiltration and redistribution model. This eliminates difficulties in solving the highly nonlinear 3D Richards equation, while the finite volume Talbot-Ogden infiltration solution is computationally efficient, guaranteed to conserve mass, and allows simulation of the effect of near-surface groundwater tables on runoff generation. The process-level components of the model are being individually tested and validated. The model as a whole will be tested on the Green River basin in Wyoming and ultimately applied to the entire Upper Colorado River basin. ADHydro development has necessitated development of tools for large-scale watershed modeling, including open-source workflow steps to extract hydromorphological information from GIS data, integrate hydrometeorological and water management forcing input, and post-processing and visualization of large output data sets. The ADHydro model will be coupled with relevant components of the NOAH-MP land surface scheme and the WRF mesoscale meteorological model. Model objectives include well documented Application Programming Interfaces (APIs) to facilitate modifications and additions by others. We will release the model as open-source in 2014 and begin establishing a users' community.

A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data sets (or cloud library) stored at Goddard.

Using multi-year reanalysis-derived recharge rates to drive a groundwater model for the Lake Tana region of Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Dokou, Z.; Kheirabadi, M.; Nikolopoulos, E. I.; Moges, S. A.; Bagtzoglou, A. C.; Anagnostou, E. N.

2017-12-01

Ethiopia's high inter-annual variability in local precipitation has resulted in droughts and floods that stress local communities and lead to economic and food insecurity. Better predictions of water availability can supply farmers and water management authorities with critical guidance, enabling informed water resource allocation and management decisions that will in turn ensure food and water security in the region. The work presented here focuses on the development and calibration of a groundwater model of the Lake Tana region, one of the most important sub-basins of the Blue Nile River Basin. Groundwater recharge, which is the major groundwater source in the area, depends mainly on the seasonality of precipitation and the spatial variation in geology. Given that land based precipitation data are sparse in the region, two approaches for estimating groundwater recharge were used and compared that both utilize global atmospheric reanalysis driven by remote sensing datasets. In the first approach, the reanalysis precipitation dataset (ECMWF reanalysis adjusted based on GPCC) together with evapotranspiration and surface run-off estimates are used to calculate the groundwater recharge component using water budget equations. In the second approach, groundwater recharge estimates (subsurface runoff) are taken directly from a Land Surface model (FLDAS Noah), provided at a monthly time scale and 0.1˚ x 0.1˚ spatial resolution. The reanalysis derived recharge rates in both cases are incorporated into the groundwater model MODFLOW, which in combination with a Lake module that simulates the Lake water budget, offers a unique capability of improving the predictability of groundwater and lake levels in the Lake Tana basin. Model simulations using the two approaches are compared against in-situ observations of groundwater and lake levels. This modeling effort can be further used to explore climate variability effects on groundwater and lake levels and provide guidance to governments and development agencies for more efficient management of the water resources of this important region. Acknowledgment: This material is based upon work supported by the National Science Foundation under Grant No. 1545874.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2007-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Retrospective Snow Analysis Across the Continental United States for the National Water Model

NASA Astrophysics Data System (ADS)

Karsten, L. R.; Gochis, D.; Dugger, A. L.; McCreight, J. L.; Barlage, M. J.; Fall, G. M.; Olheiser, C.

2016-12-01

For large portions of the United States, snow plays a vital role in hydrologic prediction. This is particularly true in the mountain west where snowmelt contributes up to 80% of total streamflow runoff. The Office of Water Prediction (OWP) will begin running the National Water Model (NWM) during the second half of 2016, which is a continental-scale implementation of the WRF-Hydro community hydrologic modeling framework. Assessing and benchmarking the performance of the snow component of the NWM is important for future research-to-operations activities and for forecasters to better understand NWM output. For this study, WRF-Hydro was ran using the same domain and physics options as the NWM (1 km LSM, 250m overland routing, and NHDPlus Version 2.1 channel network). The land surface component chosen is Noah-MP land surface model. Forcing from the National Land Data Assimilation System (NLDAS-2) was downscaled from the native 0.125 degree resolution to the 1 km modeling domain to drive the model. The model was ran over a 5-year retrospective period to gauge multi-year performance of the snow states. Output was analyzed against both in-situ observations, such as SNOTEL, and the Snow Data Assimilation System (SNODAS). In addition, gridded snow states and SNODAS grids were aggregated to Omernik-derived ecological regions. This was done in order to break up snow analysis by regions that share similar ecological and physiographic characteristics. Results show WRF-Hydro is able to capture peak timing across most of the mountain west fairly well. In terms of magnitudes, the model struggles across portions of the west with a low bias. This is especially true in the Cascades, which could be traced back to precipitation partitioning issues in the model. Across the central Rockies, the model exhibits a lower dry bias showing improved performance there. Previous literature suggests a dry bias in the precipitation out west may be contributing to model performance. East of the Rockies, the model captures events well, including both timing and magnitude when compared to SNODAS. There are issues with particular events in these regions, but this may be due to the nature of the events being mixed-phase. Overall performance with snow simulation for the NWM shows promise for use in operations.

Corruption in Higher Education: Does It Differ across the Nations and Why?

ERIC Educational Resources Information Center

Osipian, Ararat L.

2008-01-01

Corruption in higher education is a newly emerging topic in the field of education research. Some aspects of corruption in education have been addressed in recent works by Eckstein, Hallak & Poisson, Heyneman, Noah & Eckstein, Segal, and Washburn. However, rigorous systematic research is lacking. This article considers corruption in higher…

The Paluxy River Footprint Mystery--Solved.

ERIC Educational Resources Information Center

Cole, John R., Ed.; Godfrey, Laurie R., Ed.

1985-01-01

This document points out that creationists claim that humans and dinosaurs lived together in Texas just before Noah's flood by citing alleged human footprints found side-by-side with those of dinosaurs in the Cretaceous limestone of the Paluxy River near Glen Rose, Texas. An investigation was conducted to determine if this claim were true.…

Stuff the Dodos

ERIC Educational Resources Information Center

Stringer, John

2009-01-01

The author picked up a lovely greetings card the other day. The front carried a picture of an overloaded ark. The caption read "And Noah saith "Stuff the dodos"--and behold, it was so". This is an attractive but rather simplistic explanation of extinction. The author is writing in the wake of some extraordinary events, as Professor Michael Reiss,…

Kandinsky's "Composition VI": Heideggerian Poetry in Noah's Ark

ERIC Educational Resources Information Center

Hall, Joshua M.

2012-01-01

The author will begin his investigation of Wassily Kandinsky's painting "Composition VI" with Kandinsky's own commentary on the painting. He will then turn to the analysis of Kandinsky and the "Compositions" in John Sallis's book "Shades." Using this analysis as his point of departure, the author will consider how "Composition VI" resonates with…

Effects of diesel exhaust on influenza-induced nasal inflammation

EPA Science Inventory

Title: Effects of Diesel Exhaust on Influenza-Induced Nasal Inflammation T L Noah, MD1,2, K Horvath, BS3, C Robinette, RN2, 0 Diaz Sanchez, PhD4 and I Jaspers, PhD1,2. 1UNC Dept. of Pediatrics, United States; 2UNC Center for Environmental Medicine, Asthma and Lung Biology, ...

Here's Looking at You: Visual Similarity Exacerbates the Moses Illusion for Semantically Similar Celebrities

ERIC Educational Resources Information Center

Davis, Danielle K.; Abrams, Lise

2016-01-01

When people read questions like "How many animals of each kind did Moses take on the ark?", many mistakenly answer "2" despite knowing that Noah sailed the ark. This "Moses illusion" occurs when names share semantic features. Two experiments examined whether shared "visual" concepts (facial features)…

Three Early Champions of Education: Benjamin Franklin, Benjamin Rush, and Noah Webster.

ERIC Educational Resources Information Center

Blinderman, Abraham

Franklin as a stateman, Rush as a physician, and Webster as a linguist and political commentator believed in a "general diffusion of knowledge" and wrote liberally on education. They sincerely believed in education as a civilizing agent, so all three helped found schools and colleges. Franklin's interests were educational philosophy;…

A High Resolution Land Cover Data Product to Remove Urban Density Over-Estimation Bias for Coupled Urban-Vegetation-Atmosphere Interaction Studies

NASA Astrophysics Data System (ADS)

Shaffer, S. R.

2017-12-01

Coupled land-atmosphere interactions in urban settings modeled with the Weather Research and Forecasting model (WRF) derive urban land cover from 30-meter resolution National Land Cover Database (NLCD) products. However, within urban areas, the categorical NLCD lose information of non-urban classifications whenever the impervious cover within a grid cell is above 0%, and the current method to determine urban area over estimates the actual area, leading to a bias of urban contribution. To address this bias of urban contribution an investigation is conducted by employing a 1-meter resolution land cover data product derived from the National Agricultural Imagery Program (NAIP) dataset. Scenes during 2010 for the Central Arizona Phoenix Long Term Ecological Research (CAP-LTER) study area, roughly a 120 km x 100 km area containing metropolitan Phoenix, are adapted for use within WRF to determine the areal fraction and urban fraction of each WRF urban class. A method is shown for converting these NAIP data into classes corresponding to NLCD urban classes, and is evaluated in comparison with current WRF implementation using NLCD. Results are shown for comparisons of land cover products at the level of input data and aggregated to model resolution (1 km). The sensitivity of WRF short-term summertime pre-monsoon predictions within metropolitan Phoenix to different input data products of land cover, to method of aggregating these data to model grid scale (1 km), for the default and derived parameter values are examined with the Noah mosaic land surface scheme adapted for using these data. Issues with adapting these non-urban NAIP classes for use in the mosaic approach will also be discussed.

Regional statistical assessment of WRF-Hydro and IFC Model stream Flow uncertainties over the State of Iowa

NASA Astrophysics Data System (ADS)

ElSaadani, M.; Quintero, F.; Goska, R.; Krajewski, W. F.; Lahmers, T.; Small, S.; Gochis, D. J.

2015-12-01

This study examines the performance of different Hydrologic models in estimating peak flows over the state of Iowa. In this study I will compare the output of the Iowa Flood Center (IFC) hydrologic model and WRF-Hydro (NFIE configuration) to the observed flows at the USGS stream gauges. During the National Flood Interoperability Experiment I explored the performance of WRF-Hydro over the state of Iowa using different rainfall products and the resulting hydrographs showed a "flashy" behavior of the model output due to lack of calibration and bad initial flows due to short model spin period. I would like to expand this study by including a second well established hydrologic model and include more rain gauge vs. radar rainfall direct comparisons. The IFC model is expected to outperform WRF-Hydro's out of the box results, however, I will test different calibration options for both the Noah-MP land surface model and RAPID, which is the routing component of the NFIE-Hydro configuration, to see if this will improve the model results. This study will explore the statistical structure of model output uncertainties across scales (as a function of drainage areas and/or stream orders). I will also evaluate the performance of different radar-based Quantitative Precipitation Estimation (QPE) products (e.g. Stage IV, MRMS and IFC's NEXRAD based radar rainfall product. Different basins will be evaluated in this study and they will be selected based on size, amount of rainfall received over the basin area and location. Basin location will be an important factor in this study due to our prior knowledge of the performance of different NEXRAD radars that cover the region, this will help observe the effect of rainfall biases on stream flows. Another possible addition to this study is to apply controlled spatial error fields to rainfall inputs and observer the propagation of these errors through the stream network.

The Impact of AMSR-E Soil Moisture Assimilation on Evapotranspiration Estimation

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay; Mocko, David; Tian, Yudong

2012-01-01

An assessment ofETestimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 CNLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

NASA Astrophysics Data System (ADS)

Capecchi, V.; Gozzini, B.

2012-04-01

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.

Blog Comments vs. Peer Review: Which Way Makes a Book Better?

ERIC Educational Resources Information Center

Young, Jeffrey R.

2008-01-01

What if scholarly books were peer reviewed by anonymous blog comments rather than by traditional, selected peer reviewers? This is the question posed by an unusual experiment that was started recently by Noah Wardrip-Fruin, an an assistant professor of communication at the University of California at San Diego. His experiment was started after his…

Human Diversity and the Genealogy of Languages: Noah as the Founding Ancestor of the Chinese

ERIC Educational Resources Information Center

Hutton, Christopher

2008-01-01

The characteristics which were held to define the Chinese language within the Western intellectual tradition placed it for a time at the centre in discussions of the genealogy of mankind. The dominant premodern paradigm for the explanation of human linguistic diversity was Biblical exegesis, as discussed and elaborated within the framework of…

On Not Being Able to Enter Noah's Ark

ERIC Educational Resources Information Center

Adamo, Simonetta M. G.

2010-01-01

The paper describes the psychoanalytic psychotherapy of a patient who had originally been referred at the age of 15 because of his social isolation. In fact, he suffered from high-functioning Asperger's syndrome and lived in an almost delusional world populated by a number of imaginary companions, which he used to counteract a deep void and sense…

Children's Observations about the Art in Picture Books.

ERIC Educational Resources Information Center

Stewig, John Warren

This report establishes a foundation of information about how children in classroom settings develop visual literacy. Data was gathered during five 45-minute sessions with a second and a fourth grade classroom during which children looked at pictures in four versions of the Noah's Ark tale. The intent was to elicit whatever children chose to say…

The Value of Risk: Noah's Ark at the Skirball Cultural Center

ERIC Educational Resources Information Center

Bernstein, Sheri; Gittleman, Marni

2010-01-01

In this article Bernstein and Gittleman address the role of risk in creating an exhibition that is of value to the public and is aligned with their cultural institution's core values. Through an examination of the development process, the authors present lessons that can assist others who are interested in undertaking an exhibition with similar…

Modeling the Hydrological Regime of Turkana Lake (Kenya, Ethiopia) by Combining Spatially Distributed Hydrological Modeling and Remote Sensing Datasets

NASA Astrophysics Data System (ADS)

Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.

2017-12-01

Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological regime and the Lake Turkana level variability.

Prediction of heavy rainfall over Chennai Metropolitan City, Tamil Nadu, India: Impact of microphysical parameterization schemes

NASA Astrophysics Data System (ADS)

Singh, K. S.; Bonthu, Subbareddy; Purvaja, R.; Robin, R. S.; Kannan, B. A. M.; Ramesh, R.

2018-04-01

This study attempts to investigate the real-time prediction of a heavy rainfall event over the Chennai Metropolitan City, Tamil Nadu, India that occurred on 01 December 2015 using Advanced Research Weather Research and Forecasting (WRF-ARW) model. The study evaluates the impact of six microphysical (Lin, WSM6, Goddard, Thompson, Morrison and WDM6) parameterization schemes of the model on prediction of heavy rainfall event. In addition, model sensitivity has also been evaluated with six Planetary Boundary Layer (PBL) and two Land Surface Model (LSM) schemes. Model forecast was carried out using nested domain and the impact of model horizontal grid resolutions were assessed at 9 km, 6 km and 3 km. Analysis of the synoptic features using National Center for Environmental Prediction Global Forecast System (NCEP-GFS) analysis data revealed strong upper-level divergence and high moisture content at lower level were favorable for the occurrence of heavy rainfall event over the northeast coast of Tamil Nadu. The study signified that forecasted rainfall was more sensitive to the microphysics and PBL schemes compared to the LSM schemes. The model provided better forecast of the heavy rainfall event using the logical combination of Goddard microphysics, YSU PBL and Noah LSM schemes, and it was mostly attributed to timely initiation and development of the convective system. The forecast with different horizontal resolutions using cumulus parameterization indicated that the rainfall prediction was not well represented at 9 km and 6 km. The forecast with 3 km horizontal resolution provided better prediction in terms of timely initiation and development of the event. The study highlights that forecast of heavy rainfall events using a high-resolution mesoscale model with suitable representations of physical parameterization schemes are useful for disaster management and planning to minimize the potential loss of life and property.

Automated model integration at source code level: An approach for implementing models into the NASA Land Information System

NASA Astrophysics Data System (ADS)

Wang, S.; Peters-Lidard, C. D.; Mocko, D. M.; Kumar, S.; Nearing, G. S.; Arsenault, K. R.; Geiger, J. V.

2014-12-01

Model integration bridges the data flow between modeling frameworks and models. However, models usually do not fit directly into a particular modeling environment, if not designed for it. An example includes implementing different types of models into the NASA Land Information System (LIS), a software framework for land-surface modeling and data assimilation. Model implementation requires scientific knowledge and software expertise and may take a developer months to learn LIS and model software structure. Debugging and testing of the model implementation is also time-consuming due to not fully understanding LIS or the model. This time spent is costly for research and operational projects. To address this issue, an approach has been developed to automate model integration into LIS. With this in mind, a general model interface was designed to retrieve forcing inputs, parameters, and state variables needed by the model and to provide as state variables and outputs to LIS. Every model can be wrapped to comply with the interface, usually with a FORTRAN 90 subroutine. Development efforts need only knowledge of the model and basic programming skills. With such wrappers, the logic is the same for implementing all models. Code templates defined for this general model interface could be re-used with any specific model. Therefore, the model implementation can be done automatically. An automated model implementation toolkit was developed with Microsoft Excel and its built-in VBA language. It allows model specifications in three worksheets and contains FORTRAN 90 code templates in VBA programs. According to the model specification, the toolkit generates data structures and procedures within FORTRAN modules and subroutines, which transfer data between LIS and the model wrapper. Model implementation is standardized, and about 80 - 90% of the development load is reduced. In this presentation, the automated model implementation approach is described along with LIS programming interfaces, the general model interface and five case studies, including a regression model, Noah-MP, FASST, SAC-HTET/SNOW-17, and FLake. These different models vary in complexity with software structure. Also, we will describe how these complexities were overcome through using this approach and results of model benchmarks within LIS.

A Micro-Ark for Cells: Highly Open Porous Polyhydroxyalkanoate Microspheres as Injectable Scaffolds for Tissue Regeneration.

PubMed

Wei, Dai-Xu; Dao, Jin-Wei; Chen, Guo-Qiang

2018-06-19

To avoid large open surgery using scaffold transplants, small-sized cell carriers are employed to repair complexly shaped tissue defects. However, most cell carriers show poor cell adherences and viability. Therefore, polyhydroxyalkanoate (PHA), a natural biopolymer, is used to prepare highly open porous microspheres (OPMs) of 300-360 µm in diameter, combining the advantages of microspheres and scaffolds to serve as injectable carriers harboring proliferating stem cells. In addition to the convenient injection to a defected tissue, and in contrast to poor performances of OPMs made of polylactides (PLA OPMs) and traditional less porous hollow microspheres (PHA HMs), PHA OPMs present suitable surface pores of 10-60 µm and interconnected passages with an average size of 8.8 µm, leading to a high in vitro cell adhesion of 93.4%, continuous proliferation for 10 d and improved differentiation of human bone marrow mesenchymal stem cells (hMSCs). PHA OPMs also support stronger osteoblast-regeneration compared with traditional PHA HMs, PLA OPMs, commercial hyaluronic acid hydrogels, and carrier-free hMSCs in an ectopic bone-formation mouse model. PHA OPMs protect cells against stresses during injection, allowing more living cells to proliferate and migrate to damaged tissues. They function like a micro-Noah's Ark to safely transport cells to a defect tissue. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The End-to-end Demonstrator for improved decision making in the water sector in Europe (EDgE)

NASA Astrophysics Data System (ADS)

Wood, Eric; Wanders, Niko; Pan, Ming; Sheffield, Justin; Samaniego, Luis; Thober, Stephan; Kumar, Rohinni; Prudhomme, Christel; Houghton-Carr, Helen

2017-04-01

High-resolution simulations of water resources from hydrological models are vital to supporting important climate services. Apart from a high level of detail, both spatially and temporally, it is important to provide simulations that consistently cover a range of timescales, from historical reanalysis to seasonal forecast and future projections. In the new EDgE project commissioned by the ECMWF (C3S) we try to fulfill these requirements. EDgE is a proof-of-concept project which combines climate data and state-of-the-art hydrological modelling to demonstrate a water-oriented information system implemented through a web application. EDgE is working with key European stakeholders representative of private and public sectors to jointly develop and tailor approaches and techniques. With these tools, stakeholders are assisted in using improved climate information in decision-making, and supported in the development of climate change adaptation and mitigation policies. Here, we present the first results of the EDgE modelling chain, which is divided into three main processes: 1) pre-processing and downscaling; 2) hydrological modelling; 3) post-processing. Consistent downscaling and bias corrections for historical simulations, seasonal forecasts and climate projections ensure that the results across scales are robust. The daily temporal resolution and 5km spatial resolution ensure locally relevant simulations. With the use of four hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), uncertainty between models is properly addressed, while consistency is guaranteed by using identical input data for static land surface parameterizations. The forecast results are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs) that have been created in collaboration with the end-user community of the EDgE project. The final product of this project is composed of 15 years of seasonal forecast and 10 climate change projections, all combined with four hydrological models. These unique high-resolution climate information simulations in the EDgE project provide an unprecedented information system for decision-making over Europe.

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

NASA Astrophysics Data System (ADS)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

The Legs Problem--For All Ages

ERIC Educational Resources Information Center

Way, Jenni

2005-01-01

This article presents an example of a versatile multi-solution problem that can be used right across the primary years. The basic problem is: "Noah saw 16 legs go past him into the Ark. How many creatures did he see?" Any even number can be used, although, 2 legs allows only one answer and with 16 legs there are already 14 different…

Beyond the Search for Truth: Dewey's Humble and Humanistic Vision of Science Education

ERIC Educational Resources Information Center

Waddington, David I.; Feinstein, Noah Weeth

2016-01-01

In this essay, David Waddington and Noah Weeth Feinstein explore how Dewey's conception of science can help us rethink the way science is done in schools. The authors begin by contrasting a view of science that is implicitly accepted by many scientists and science educators--science as a search for truth--with Dewey's instrumentalist,…

Maximizing phylogenetic diversity in biodiversity conservation: Greedy solutions to the Noah's Ark problem.

PubMed

Hartmann, Klaas; Steel, Mike

2006-08-01

The Noah's Ark Problem (NAP) is a comprehensive cost-effectiveness methodology for biodiversity conservation that was introduced by Weitzman (1998) and utilizes the phylogenetic tree containing the taxa of interest to assess biodiversity. Given a set of taxa, each of which has a particular survival probability that can be increased at some cost, the NAP seeks to allocate limited funds to conserving these taxa so that the future expected biodiversity is maximized. Finding optimal solutions using this framework is a computationally difficult problem to which a simple and efficient "greedy" algorithm has been proposed in the literature and applied to conservation problems. We show that, although algorithms of this type cannot produce optimal solutions for the general NAP, there are two restricted scenarios of the NAP for which a greedy algorithm is guaranteed to produce optimal solutions. The first scenario requires the taxa to have equal conservation cost; the second scenario requires an ultrametric tree. The NAP assumes a linear relationship between the funding allocated to conservation of a taxon and the increased survival probability of that taxon. This relationship is briefly investigated and one variation is suggested that can also be solved using a greedy algorithm.

Pilot study on the use of data mining to identify cochlear implant candidates.

PubMed

Grisel, Jedidiah J; Schafer, Erin; Lam, Anne; Griffin, Terry

2018-05-01

The goal of this pilot study was to determine the clinical utility of data-mining software that screens for cochlear implant (CI) candidacy. The Auditory Implant Initiative developed a software module that screens for CI candidates via integration with a software system (Noah 4) that serves as a depository for hearing test data. To identify candidates, patient audiograms from one practice were exported into the screening module. Candidates were tracked to determine if any eventually underwent implantation. After loading 4836 audiograms from the Noah 4 system, the screening module identified 558 potential CI candidates. After reviewing the data for the potential candidates, 117 were targeted and invited to an educational event. Following the event, a total of six candidates were evaluated, and two were implanted. This objective approach to identifying candidates has the potential to address the gross underutilization of CIs by removing any bias or lack of knowledge regarding the management of severe to profound sensorineural hearing loss with CIs. The screening module was an effective tool for identifying potential CI candidates at one ENT practice. On a larger scale, the screening module has the potential to impact thousands of CI candidates worldwide.

Monitoring groundwater storage changes in the highly seasonal humid tropics: Validation of GRACE measurements in the Bengal Basin

NASA Astrophysics Data System (ADS)

Shamsudduha, M.; Taylor, R. G.; Longuevergne, L.

2012-02-01

Satellite monitoring of changes in terrestrial water storage provides invaluable information regarding the basin-scale dynamics of hydrological systems where ground-based records are limited. In the Bengal Basin of Bangladesh, we test the ability of satellite measurements under the Gravity Recovery and Climate Experiment (GRACE) to trace both the seasonality and trend in groundwater storage associated with intensive groundwater abstraction for dry-season irrigation and wet-season (monsoonal) recharge. We show that GRACE (CSR, GRGS) datasets of recent (2003 to 2007) groundwater storage changes (ΔGWS) correlate well (r = 0.77 to 0.93, p value < 0.0001) with in situ borehole records from a network of 236 monitoring stations and account for 44% of the total variation in terrestrial water storage (ΔTWS); highest correlation (r = 0.93, p value < 0.0001) and lowest root-mean-square error (<4 cm) are realized using a spherical harmonic product of CSR. Changes in surface water storage estimated from a network of 298 river gauging stations and soil-moisture derived from Land Surface Models explain 22% and 33% of ΔTWS, respectively. Groundwater depletion estimated from borehole hydrographs (-0.52 ± 0.30 km3 yr-1) is within the range of satellite-derived estimates (-0.44 to -2.04 km3 yr-1) that result from uncertainty associated with the simulation of soil moisture (CLM, NOAH, VIC) and GRACE signal-processing techniques. Recent (2003 to 2007) estimates of groundwater depletion are substantially greater than long-term (1985 to 2007) mean (-0.21 ± 0.03 km3 yr-1) and are explained primarily by substantial increases in groundwater abstraction for the dry-season irrigation and public water supplies over the last two decades.

Changes in the atmospheric evaporative demand in Mexico

NASA Astrophysics Data System (ADS)

Agustin Brena-Naranjo, Jose; Pedrozo-Acuña, Adrian; Laverde-Barajas, Miguel

2015-04-01

An important driver of the hydrological cycle is the atmospheric evaporative demand (AED). Previous studies using measurements of evaporation in pans have found evidence that AED has been declining over the second half of the 20th century. Such trends have been mostly attributed to a global decline in near surface wind speed (mainly driven by changes in land cover such as the terrestrial surface roughness) whereas other variables controlling AED such as the vapor pressure deficit, solar radiation and air temperature having a more limited role (such changes are driven by long-term climatic variations). The objective of this work is to assess the temporal and spatial observed changes in pan evaporation in 151 meteorological stations located across Mexico for the period 1961-2010. The stations were located on a climatic gradient, with aridity indexes ranging between 0.3 and 10. The radiative and aerodynamic controls attributed to the observed trends are analyzed with outputs by the Noah model from the Global Land Data Assimilation System (GLDAS). The results show a consistent decline in annual pan evaporation between 1961 and 1992 whereas the trend was reverted from 1992 until 2010. Statistically significant negative changes using the non-parametric Mann-Kendall test were found in 43% of the stations for the 1961-1992 and 20% for 1992-2010, respectively. Among the climatological variables extracted from GLDAS, it was the annual wind speed that gave the highest statistical correlation. This work agrees with previous studies in other regions of the world suggesting that pan evaporation has been on average declining until 1990 followed by a slightly positive trend during the last twenty years. Finally, we show that the magnitude of change in those regions dominated by wind and those dominated by radiative processes are strongly different.

Real-Time System for Water Modeling and Management

NASA Astrophysics Data System (ADS)

Lee, J.; Zhao, T.; David, C. H.; Minsker, B.

2012-12-01

Working closely with the Texas Commission on Environmental Quality (TCEQ) and the University of Texas at Austin (UT-Austin), we are developing a real-time system for water modeling and management using advanced cyberinfrastructure, data integration and geospatial visualization, and numerical modeling. The state of Texas suffered a severe drought in 2011 that cost the state $7.62 billion in agricultural losses (crops and livestock). Devastating situations such as this could potentially be avoided with better water modeling and management strategies that incorporate state of the art simulation and digital data integration. The goal of the project is to prototype a near-real-time decision support system for river modeling and management in Texas that can serve as a national and international model to promote more sustainable and resilient water systems. The system uses National Weather Service current and predicted precipitation data as input to the Noah-MP Land Surface model, which forecasts runoff, soil moisture, evapotranspiration, and water table levels given land surface features. These results are then used by a river model called RAPID, along with an error model currently under development at UT-Austin, to forecast stream flows in the rivers. Model forecasts are visualized as a Web application for TCEQ decision makers, who issue water diversion (withdrawal) permits and any needed drought restrictions; permit holders; and reservoir operation managers. Users will be able to adjust model parameters to predict the impacts of alternative curtailment scenarios or weather forecasts. A real-time optimization system under development will help TCEQ to identify optimal curtailment strategies to minimize impacts on permit holders and protect health and safety. To develop the system we have implemented RAPID as a remotely-executed modeling service using the Cyberintegrator workflow system with input data downloaded from the North American Land Data Assimilation System. The Cyberintegrator workflow system provides RESTful web services for users to provide inputs, execute workflows, and retrieve outputs. Along with REST endpoints, PAW (Publishable Active Workflows) provides the web user interface toolkit for us to develop web applications with scientific workflows. The prototype web application is built on top of workflows with PAW, so that users will have a user-friendly web environment to provide input parameters, execute the model, and visualize/retrieve the results using geospatial mapping tools. In future work the optimization model will be developed and integrated into the workflow.; Real-Time System for Water Modeling and Management

NASA Applied Sciences Program

NASA Technical Reports Server (NTRS)

Estes, Sue M.; Haynes, J. A.

2009-01-01

NASA's strategic Goals: a) Develop a balanced overall program of science, exploration, and aeronautics consistent with the redirection of human spaceflight program to focus on exploration. b) Study Earth from space to advance scientific understanding and meet societal needs. NASA's partnership efforts in global modeling and data assimilation over the next decade will shorten the distance from observations to answers for important, leading-edge science questions. NASA's Applied Sciences program will continue the Agency's efforts in benchmarking the assimilation of NASA research results into policy and management decision-support tools that are vital for the Nation's environment, economy, safety, and security. NASA also is working with NOAH and inter-agency forums to transition mature research capabilities to operational systems, primarily the polar and geostationary operational environmental satellites, and to utilize fully those assets for research purposes.

Probabilistic Water Availability Prediction in the Rio Grande Basin using Large-scale Circulation Indices as Precursor

NASA Astrophysics Data System (ADS)

Khedun, C. P.; Mishra, A. K.; Giardino, J. R.; Singh, V. P.

2011-12-01

Hydrometeorological conditions, and therefore water availability, is affected by large-scale circulation indices. In the Rio Grande, which is a transboundary basin shared between the United States and Mexico, the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) influence local hydrological conditions. Different sub-regions of the basin exhibit varying degrees of correlation, but in general, an increase (decrease) in runoff during El Niños (La Niñas) is noted. Positive PDO enhances the effect of El Niño and dampens the negative effect of La Niña, and when it is in its neutral/transition phase, La Niña dominates climatic conditions and reduces water availability. Further, lags of up to 3 months have been found between ENSO and precipitation in the basin. We hypothesize that (1) a trivariate statistical relationship can be established between the two climate indices and water availability, and (2) the relationship can be used to predict water availability based on projected PDO and ENSO conditions. We use copula to establish the dependence between climate indices and water availability. Water availability is generated from Noah land surface model (LSM), forced with the North American Land Data Assimilation System Phase 2 (NLDAS-2). The model is run within NASA GSFC's Land Information System. LSM generated runoff gives a more realistic picture of available surface water as it is not affected by anthropogenic changes, such as the construction of dams, diversions, and other land use land cover changes, which may obscure climatic influences. Marginals from climate indices and runoff are from different distribution families, thus conventional functional forms of multivariate frequency distributions cannot be employed. Copulas offer a viable alternative as marginals from different families can be combined into a joint distribution. Uncertainties in the statistical relationship can be determined and the statistical model can be used for prediction purposes. The outcome of the study can provide advanced warning on the expected state of surface water, based on projected ENSO and PDO conditions. Such warning may help trigger drought management plans in both the US and Mexico for example, and ensure the long-term sustainable management of water in the basin.

GLEAM v3: updated land evaporation and root-zone soil moisture datasets

NASA Astrophysics Data System (ADS)

Martens, Brecht; Miralles, Diego; Lievens, Hans; van der Schalie, Robin; de Jeu, Richard; Fernández-Prieto, Diego; Verhoest, Niko

2016-04-01

Evaporation determines the availability of surface water resources and the requirements for irrigation. In addition, through its impacts on the water, carbon and energy budgets, evaporation influences the occurrence of rainfall and the dynamics of air temperature. Therefore, reliable estimates of this flux at regional to global scales are of major importance for water management and meteorological forecasting of extreme events. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to the limited global coverage of in situ measurements. Remote sensing techniques can help to overcome the lack of ground data. However, evaporation is not directly observable from satellite systems. As a result, recent efforts have focussed on combining the observable drivers of evaporation within process-based models. The Global Land Evaporation Amsterdam Model (GLEAM, www.gleam.eu) estimates terrestrial evaporation based on daily satellite observations of meteorological drivers of terrestrial evaporation, vegetation characteristics and soil moisture. Since the publication of the first version of the model in 2011, GLEAM has been widely applied for the study of trends in the water cycle, interactions between land and atmosphere and hydrometeorological extreme events. A third version of the GLEAM global datasets will be available from the beginning of 2016 and will be distributed using www.gleam.eu as gateway. The updated datasets include separate estimates for the different components of the evaporative flux (i.e. transpiration, bare-soil evaporation, interception loss, open-water evaporation and snow sublimation), as well as variables like the evaporative stress, potential evaporation, root-zone soil moisture and surface soil moisture. A new dataset using SMOS-based input data of surface soil moisture and vegetation optical depth will also be distributed. The most important updates in GLEAM include the revision of the soil moisture data assimilation system, the evaporative stress functions and the infiltration of rainfall. In this presentation, we will highlight the changes of the methodology and present the new datasets, their validation against in situ observations and the comparisons against alternative datasets of terrestrial evaporation, such as GLDAS-Noah, ERA-Interim and previous GLEAM datasets. Preliminary results indicate that the magnitude and the spatio-temporal variability of the evaporation estimates have been slightly improved upon previous versions of the datasets.

Acoustically Tailored Composite Rotorcraft Fuselage Panels

DTIC Science & Technology

2015-07-02

In this work, we have developed and demonstrated technologies and methodologies for designing composite fuselage panels which radiate less sound...SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) NASA Langley Rsearch Center ATTN: Mr. Noah Schiller Structural Acoustics Branch Mail Stop 463 Hampton...500 Hz. The panels were designed to withstand structural loading from normal rotorcraft operation, as well as ’man-on-the-roof static loads

Question Generation via Overgenerating Transformations and Ranking

DTIC Science & Technology

2009-01-01

School of Computer Science Carnegie Mellon University 5000 Forbes Ave., Pittsburgh, PA 15213 www.lti.cs.cmu.edu c©2009, Michael Heilman and Noah A...PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Carnegie Mellon University ,School of Computer Science,5000 Forbes Ave,Pittsburgh,PA,15213 8...1967), in particular those that view a question as a transformation of a canonical declarative sentence ( Chomsky , 1973). In computational linguistics

National Scale Rainfall Map Based on Linearly Interpolated Data from Automated Weather Stations and Rain Gauges

NASA Astrophysics Data System (ADS)

Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay

2014-05-01

In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the Marikina River, the local officials used this information and determined that the river would overflow in a few hours. It gave them a critical lead time to evacuate residents along the floodplain and no casualties were reported after the event.

The effect of the Asian Monsoon to the atmospheric boundary layer over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Li, Maoshan; Su, Zhongbo; Chen, Xuelong; Zheng, Donghai; Sun, Fanglin; Ma, Yaoming; Hu, Zeyong

2016-04-01

Modulation of the diurnal variations in the convective activities associated with day-by-day changes of surface flux and soil moisture was observed in the beginning of the monsoon season on the central Tibetan plateau (Sugimoto et al., 2008) which indicates the importance of land-atmosphere interactions in determining convective activities over the Tibetan plateau. Detailed interaction processes need to be studied by experiments designed to evaluate a set of hypotheses on mechanisms and linkages of these interactions. A possible function of vegetation to increase precipitation in cases of Tibetan High type was suggested by Yamada and Uyeda (2006). Use of satellite derived plateau scale soil moisture (Wen et al., 2003) enables the verification of these hypotheses (e.g. Trier et al. 2004). To evaluate these feedbacks, the mesoscale WRF model will be used because several numerical experiments are being conducted to improve the soil physical parameterization in the Noah land surface scheme in WRF so that the extreme conditions on the Tibetan plateau could be adequately represented (Van der Velde et al., 2009) such that the impacts on the structure of the atmospheric boundary layer can be assessed and improved. The Tibetan Observational Research Platform (TORP) operated by the Institute of Tibetan Plateau (Ma et al., 2008) will be fully utilized to study the characteristics of the plateau climate and different aspects of the WRF model will be evaluated using this extensive observation platform (e.g. Su et al., 2012). Recently, advanced studies on energy budget have been done by combining field and satellite measurements over the Tibetan Plateau (e.g. Ma et al., 2005). Such studies, however, were based on a single satellite observation and for a few days over an annual cycle, which are insufficient to reveal the relation between the land surface energy budget and the Asian monsoon over the Tibetan plateau. Time series analysis of satellite observations will provide the needed temporal and spatial coupling and means for validation of mesoscale model simulations (Zhong et al., 2009, 2011). When these time series are integrated into energy balance analyses methods (Su, 2002, 2005) with reanalysis data, plateau scale diurnal radiative and turbulence fluxes can be generated (Oku et al., 2005; Su et al., 2010) for the study of the boundary layer atmospheric structures at plateau scale. As such regional land-atmosphere feedbacks and atmospheric boundary layer structures can be studied. The quantification of the multi-scale atmospheric boundary layer and land surface processes over the heterogeneous underlying surface of the Tibetan Plateau is a challenging problem that remains unsettled despite many years of efforts. Using field observation, truth investigation, land surface process parameterization and meso-scale simulation, the dynamical and thermal uniform function of the atmospheric boundary layer and its effect to the atmospheric boundary layer will be analyzed in this research. Results The different characteristics of the Boundary layer with Asia monsoon season exchange over TP The height of atmospheric boundary layer was higher before monsoon season than it in summer. It was around 3-4 km above the ground in spring, while it was 1-2 km during monsoon season. It due to sensible heat flux was stronger in spring than it in summer. Using wavelet analysis method, we decomposed the wind include horizontal and vertical velocity from radiosounding observational data. The reason of high boundary layer height was disclosed. Compared to the observation, the output of model was underestimation during spring, while it was reasonable in summer monsoon. The effect of the Asian Monsoon to the precipitation on the TP Numerical simulation of climate on the TP was implemented for the whole year of 2008 using WRF-Noah model. The output of the WRF model is compared to TRMM data set for precipitation and ERA-interim land product for soil moisture. Modeled precipitation was greater than TRMM observes except for southwest of the TP. The modeled results are good agreement with TRMM data. The mean bias is around 22 mm/month and the standard deviation is around 30. More detailed statistics analysis will be done in the near future. The precipitation of convective increased from Jan. to June and arrives to the maximum of 36 percent in July, then decreases. It was obviously that the convective activity was strong during monsoon season. The monthly total precipitation extents from southeast to northwest with summer monsoon arrived at TP and it is largest in July. Figure 10 shows that there is positive absolute verticity at 500 mb, but it is response on that it exist a negative potential verticity at 300 mb on the TP. Acknowledgments We would like to thank Prof. Su for the valuable advice and support. We would also like to thank all staff of water resources department and my colleague, Xuelong Chen, Donghai Zheng, Yijian Zeng, Shaoning Lv, Cunbo Han et al. for their encouragement and guidance. I appreciate Dr. Joris for his technical support on workstation. This work was supported by the National Natural Science Foundation of China (Grant Nos. 91337212, 41175008), Cold and Arid Regions Environmental and Engineering Research Institute Youth Science Tech-nology Service Network initiative (STS), the China Exchange Project (Grant No. 13CDP007), and the National Natural Science Foundation of China (Grant Nos. 40825015 and 40675012). The authors thank all colleagues and engineers who contributed to the field observations at the NPCE-BJ station.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Arsenault, K. R.; Shukla, S.; Getirana, A.; McNally, A.; Koster, R. D.; Zaitchik, B. F.; Badr, H. S.; Roningen, J. M.; Kumar, S.; Funk, C. C.

2017-12-01

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA's web-services. The water deficit forecasting system thus far incorporates NASA GMAO's Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. Comparison of the models' energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology. The system uses seasonal climate forecasts from NASA's GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP's Climate Forecast System-2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests that for the Blue Nile basin, (1) the combination of GEOS-5 and CFSv2 is equivalent in skill to the full North American Multimodel Ensemble (NMME); and (2) the seasonal water deficit forecasting system skill for both soil moisture and streamflow anomalies is greater than the standard Ensemble Streamflow Prediction (ESP) approach.

Moisture balance over the Iberian Peninsula computed using a high resolution regional climate model. The impact of 3DVAR data assimilation.

NASA Astrophysics Data System (ADS)

González-Rojí, Santos J.; Sáenz, Jon; Ibarra-Berastegi, Gabriel

2016-04-01

A numerical downscaling exercise over the Iberian Peninsula has been run nesting the WRF model inside ERA Interim. The Iberian Peninsula has been covered by a 15km x 15 km grid with 51 vertical levels. Two model configurations have been tested in two experiments spanning the period 2010-2014 after a one year spin-up (2009). In both cases, the model uses high resolution daily-varying SST fields and the Noah land surface model. In the first experiment (N), after the model is initialised, boundary conditions drive the model, as usual in numerical downscaling experiments. The second experiment (D) is configured the same way as the N case, but 3DVAR data assimilation is run every six hours (00Z, 06Z, 12Z and 18Z) using observations obtained from the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations) using a 120' window around analysis times. For the data assimilation experiment (D), seasonally (monthly) varying background error covariance matrices have been prepared according to the parameterisations used and the mesoscale model domain. For both N and D runs, the moisture balance of the model runs has been evaluated over the Iberian Peninsula, both internally according to the model results (moisture balance in the model) and also in terms of the observed moisture fields from observational datasets (particularly precipitable water and precipitation from observations). Verification has been performed both at the daily and monthly time scales. The verification has also been performed for ERA Interim, the driving coarse-scale dataset used to drive the regional model too. Results show that the leading terms that must be considered over the area are the tendency in the precipitable water column, the divergence of moisture flux, evaporation (computed from latent heat flux at the surface) and precipitation. In the case of ERA Interim, the divergence of Qc is also relevant, although still a minor player in the moisture balance. Both mesoscale model runs are more effective at closing the moisture balance over the whole Iberian Peninsula than ERA Interim. The N experiment (no data assimilation) shows a better closure than the D case, as could be expected from the lack of analysis increments in it. This result is robust both at the daily and monthly time scales. Both ERA Interim and the D experiment produce a negative residual in the balance equation (compatible with excess evaporation or increased convergence of moisture over the Iberian Peninsula). This is a result of the data assimilation process in the D dataset, since in the N experiment the residual is mainly positive. The seasonal cycle of evaporation is much closer in the D experiment to the one in ERA Interim than in the N case, with a higher evaporation during summer months. However, both regional climate model runs show a lower evaporation rate than ERA Interim, particularly during summer months.

Engineering chimeras for Noah's ark.

PubMed

Dixon, B

1984-04-01

Chimeras, or animals containing the tissues of two or more distinct genetic types, have been successfully created from goat-sheep combinations by research teams at the ARC Institute of Animal Physiology in Cambridge, England, and the Justus-Liebig-Universitat in Giessen, West Germany. Dixon describes the methods used in this research and goes on to discuss the future potential for creating true hybrids capable of reproducing themselves, perhaps even involving human-animal combinations.

Modeling complex systems in the geosciences

NASA Astrophysics Data System (ADS)

Balcerak, Ernie

2013-03-01

Many geophysical phenomena can be described as complex systems, involving phenomena such as extreme or "wild" events that often do not follow the Gaussian distribution that would be expected if the events were simply random and uncorrelated. For instance, some geophysical phenomena like earthquakes show a much higher occurrence of relatively large values than would a Gaussian distribution and so are examples of the "Noah effect" (named by Benoit Mandelbrot for the exceptionally heavy rain in the biblical flood). Other geophysical phenomena are examples of the "Joseph effect," in which a state is especially persistent, such as a spell of multiple consecutive hot days (heat waves) or several dry summers in a row. The Joseph effect was named after the biblical story in which Joseph's dream of seven fat cows and seven thin ones predicted 7 years of plenty followed by 7 years of drought.

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

NASA Astrophysics Data System (ADS)

Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

2015-12-01

The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

Streamflow Impacts of Biofuel Policy-Driven Landscape Change

PubMed Central

Khanal, Sami; Anex, Robert P.; Anderson, Christopher J.; Herzmann, Daryl E.

2014-01-01

Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979–2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity. PMID:25289698

Decomposition of Sources of Errors in Seasonal Streamflow Forecasting over the U.S. Sunbelt

NASA Technical Reports Server (NTRS)

Mazrooei, Amirhossein; Sinah, Tusshar; Sankarasubramanian, A.; Kumar, Sujay V.; Peters-Lidard, Christa D.

2015-01-01

Seasonal streamflow forecasts, contingent on climate information, can be utilized to ensure water supply for multiple uses including municipal demands, hydroelectric power generation, and for planning agricultural operations. However, uncertainties in the streamflow forecasts pose significant challenges in their utilization in real-time operations. In this study, we systematically decompose various sources of errors in developing seasonal streamflow forecasts from two Land Surface Models (LSMs) (Noah3.2 and CLM2), which are forced with downscaled and disaggregated climate forecasts. In particular, the study quantifies the relative contributions of the sources of errors from LSMs, climate forecasts, and downscaling/disaggregation techniques in developing seasonal streamflow forecast. For this purpose, three month ahead seasonal precipitation forecasts from the ECHAM4.5 general circulation model (GCM) were statistically downscaled from 2.8deg to 1/8deg spatial resolution using principal component regression (PCR) and then temporally disaggregated from monthly to daily time step using kernel-nearest neighbor (K-NN) approach. For other climatic forcings, excluding precipitation, we considered the North American Land Data Assimilation System version 2 (NLDAS-2) hourly climatology over the years 1979 to 2010. Then the selected LSMs were forced with precipitation forecasts and NLDAS-2 hourly climatology to develop retrospective seasonal streamflow forecasts over a period of 20 years (1991-2010). Finally, the performance of LSMs in forecasting streamflow under different schemes was analyzed to quantify the relative contribution of various sources of errors in developing seasonal streamflow forecast. Our results indicate that the most dominant source of errors during winter and fall seasons is the errors due to ECHAM4.5 precipitation forecasts, while temporal disaggregation scheme contributes to maximum errors during summer season.

Analysis of Defenses Against Code Reuse Attacks on Modern and New Architectures

DTIC Science & Technology

2015-09-01

soundness or completeness. An incomplete analysis will produce extra edges in the CFG that might allow an attacker to slip through. An unsound analysis...Analysis of Defenses Against Code Reuse Attacks on Modern and New Architectures by Isaac Noah Evans Submitted to the Department of Electrical...Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Engineering in Electrical Engineering and Computer

Prediction Markets for Defense Acquisition: The Devil is in the Details

DTIC Science & Technology

2010-05-01

1 Bill Gates, Pete Coughlan, Noah Myung, Jeremy Arkes Professors of Economics Naval Postgraduate School Prediction Markets for Defense Acquisition...Acquisition: The Devil is in the Details 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e...TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School,Monterey,CA,93943 8. PERFORMING

A comparison of daily evaporation downscaled using WRFDA model and GLEAM dataset over the Iberian Peninsula.

NASA Astrophysics Data System (ADS)

José González-Rojí, Santos; Sáenz, Jon; Ibarra-Berastegi, Gabriel

2017-04-01

GLEAM dataset was presented a few years ago and since that moment, it has just been used for validation of evaporation in a few places of the world (Australia and Africa). The Iberian Peninsula is composed of different soil types and it is affected by different weather regimes, with different climate regions. It is this feature which makes it a very interesting zone for the study of the meteorological cycle, including evaporation. For that purpose, a numerical downscaling exercise over the Iberian Peninsula was run nesting the WRF model inside ERA Interim. Two model configurations were tested in two experiments spanning the period 2010-2014 after a one-year spin-up (2009). In the first experiment (N), boundary conditions drive the model. The second experiment (D) is configured the same way as the N case, but 3DVAR data assimilation is run every six hours (00Z, 06Z, 12Z and 18Z) using observations obtained from the PREPBUFR dataset. For both N and D runs and ERA Interim, the evaporation of the model runs was compared to GLEAM v3.0b and v3.0c datasets over the Iberian Peninsula, both at the daily and monthly time scales. GLEAM v3.0a was not used for validation as it uses for forcing radiation and air temperature data from ERA Interim. Results show that the experiment with data assimilation (D) improve the results obtained for N experiment. Moreover, correlations values are comparable to the ones obtained with ERA Interim. However, some negative correlation values are observed at Portuguese and Mediterranean coasts for both WRF runs. All of these problematic points are considered as urban sites by the NOAH land surface model. Because of that, the model is not able to simulate a correct evaporation value. Even with these discrepancies, better results than for ERA Interim are observed for seasonal Biases and daily RMSEs over Iberian Peninsula, obtaining the best values inland. Minimal differences are observed for the two GLEAM datasets selected.

Trace Metals in Noah's Ark Shells (Arca noae Linnaeus, 1758): Impact of Tourist Season and Human Health Risk.

PubMed

Ivanković, Dušica; Erk, Marijana; Župan, Ivan; Čulin, Jelena; Dragun, Zrinka; Bačić, Niko; Cindrić, Ana-Marija

2016-10-01

Commercially important bivalve Noah's Ark shell (Arca noae Linnaeus, 1758) represents a high-quality seafood product, but the data on levels of metal contaminants that could pose a human health risk and also on some essential elements that are important for health protection are lacking. This study examined the concentrations of Cd, Pb, Cr, Ni, Cu, Co, and Zn in the soft tissue of A. noae from harvesting area in the central Adriatic Sea, to survey whether heavy metals are within the acceptable limits for public health and whether tourism could have an impact on them. The concentrations of analysed metals varied for Cd: 0.15-0.74, Pb: 0.06-0.26, Cr: 0.11-0.34, Ni: 0.09-0.22, Cu: 0.65-1.95, Co: 0.04-0.09, and Zn: 18.3-74.7 mg/kg wet weight. These levels were lower than the permissible limits for safe consummation of seafood, and only for Cd, some precautions should be taken into account if older shellfish were consumed. Increase of Cd, Cr, and Cu in shell tissue was observed during the tourist season at the site closest to the marine traffic routes, indicating that metal levels in shellfish tissue should be monitored especially carefully during the peak tourist season to prevent eventual toxic effects due to increased intake of metals, specifically of Cd.

4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

2015-01-01

This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.

Streamflow forecasting and data assimilation: bias in precipitation, soil moisture states, and groundwater fluxes.

NASA Astrophysics Data System (ADS)

McCreight, J. L.; Gochis, D. J.; Hoar, T.; Dugger, A. L.; Yu, W.

2014-12-01

Uncertainty in precipitation forcing, soil moisture states, and model groundwater fluxes are first-order sources of error in streamflow forecasting. While near-surface estimates of soil moisture are now available from satellite, very few soil moisture observations below 5 cm depth or groundwater discharge estimates are available for operational forecasting. Radar precipitation estimates are subject to large biases, particularly during extreme events (e.g. Steiner et al., 2010) and their correction is not typically available in real-time. Streamflow data, however, are readily available in near-real-time and can be assimilated operationally to help constrain uncertainty in these uncertain states and improve streamflow forecasts. We examine the ability of streamflow observations to diagnose bias in the three most uncertain variables: precipitation forcing, soil moisture states, and groundwater fluxes. We investigate strategies for their subsequent bias correction. These include spinup and calibration strategies with and without the use of data assimilation and the determination of the proper spinup timescales. Global and spatially distributed multipliers on the uncertain states included in the assimilation state vector (e.g. Seo et al., 2003) will also be evaluated. We examine real cases and observing system simulation experiments for both normal and extreme rainfall events. One of our test cases considers the Colorado Front Range flood of September 2013 where the range of disagreement amongst five precipitation estimates spanned a factor of five with only one exhibiting appreciable positive bias (Gochis et al, submitted). Our experiments are conducted using the WRF-Hydro model with the NoahMP land surface component and the data assimilation research testbed (DART). A variety of ensemble data assimilation approaches (filters) are considered. ReferencesGochis, DJ, et al. "The Great Colorado Flood of September 2013" BAMS (Submitted 4-7-14). Seo, DJ, V Koren, and N Cajina. "Real-time variational assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting." J Hydromet (2003). Steiner, Matthias, JA Smith, SJ Burges, CV Alonso, and RW Darden. "Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation." WRR (1999).

Changes in Urban Climate due to Future Land-Use Changes based on Population Changes in the Nagoya Region

NASA Astrophysics Data System (ADS)

Adachi, S. A.; Hara, M.; Takahashi, H. G.; Ma, X.; Yoshikane, T.; Kimura, F.

2013-12-01

Severe hot weather in summer season becomes a big social problem in metropolitan areas, including the Nagoya region in Japan. Surface air temperature warming is projected in the future. Therefore, the reduction of surface air temperature is an urgent issue in the urban area. Although there are several studies dealing with the effects of global climate change and urbanization to the local climate in the future, these studies tend to ignore the future population changes. This study estimates future land-use scenarios associated with the multi-projections of future population and investigates the impacts of these scenarios on the surface temperature change. The Weather Research and Forecast model ver. 3.3.1 (hereafter, WRF) was used in this study. The horizontal resolutions were 20km, 4km, and 2km, for outer, middle, and inner domains, respectively. The results from the inner domain, covering the Nagoya region, were used for the analysis. The Noah land surface model and the single-layer urban canopy model were applied to calculate the land surface processes and urban surface processes, respectively. The initial and boundary conditions were given from the NCEP/NCAR reanalysis data in August 2010. The urban area ratio used in the WRF model was calculated from the future land-use data provided by the S8 project. The land-use data was created as follows. (1) Three scenarios of population, namely, with high-fertility assumption and low-mortality assumption (POP-high), with medium-fertility assumption and medium-mortality assumption (POP-med), and with low-fertility assumption and high-mortality assumption (POP-low), are estimated using the method proposed by Ariga and Matsuhashi (2012). These scenarios are based on the future projections provided by the National Institute of Population and Social Security Research. (2) The future changes in urban area ratio were assumed to be proportional to the population change (Hanasaki et al., 2012). The averaged urban area ratio in the Nagoya region was 0.37 in 2010. The area ratios were projected to reach a peak in 2010 to 2020, and then to decrease in the future in all of scenarios. The urban heat island intensity in the Nagoya region is about 1.5°C in 2010. In contrast, the differences of surface temperature is -0.17°C, -0.21°C, and -0.30°C in POP-high, POP-med, and POP-low, from the current situation in 2010. These impacts correspond to the 10% to 20% of current urban heat island intensity. However, the changes in the efficiency of energy consumption were not considered. Considering that the future surface temperature change is projected to be about 1.2°C to 4°C in 2070, it is required to quantitatively evaluate future urban scenarios including the mitigation strategies for urban heat island such as the improvement of energy consumption, greening, and so on. Acknowledgments. This study was supported by the Research Program on Climate Change Adaptation (RECCA) Fund by Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan and the Global Environment Research Fund (S-8) of the Ministry of the Environment of Japan.

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

NASA Astrophysics Data System (ADS)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios - (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) - are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

Monitoring groundwater storage changes in the highly dynamic Bengal Basin: validation of GRACE measurements

NASA Astrophysics Data System (ADS)

Shamsudduha, M.; Taylor, R. G.; Longuevergne, L.

2011-12-01

Monitoring of spatio-temporal changes in terrestrial water storage (ΔTWS) provides valuable information regarding the basin-scale dynamics of hydrological systems. Recent satellite measurements of the ΔTWS under the Gravity Recovery and Climate Experiment (GRACE) enable the derivation of groundwater storage changes (ΔGWS) where in situ data are limited. In the well monitored and highly-dynamic Bengal Basin of Bangladesh, we test the ability of GRACE measurements to trace the seasonality and trend in groundwater storage associated with intensive groundwater abstraction for dry-season irrigation and wet-season (monsoonal) recharge. Two different GRACE products (CSR and GRGS) and data processing methods (gridded and spherical harmonics) are also compared. Results show that GRACE derived estimates of recent (2003 to 2007) ΔGWS correlate well (r=0.77 to 0.93, p-value <0.0001) with borehole-derived estimates from a network of 236 monitoring stations in Bangladesh. The highest correlation (r=0.93, p-value <0.0001) and lowest root mean square error (<4 cm) are realized using a spherical harmonic product of CSR for these estimates. ΔGWS accounts for 44% of the total variation in ΔTWS in the Bengal Basin. Changes in surface water storage (ΔSWS) estimated from a network of 298 river gauging stations and soil moisture storage (ΔSMS) derived from Land Surface Models explain 22% and 33% of ΔTWS respectively. Groundwater depletion estimated from borehole hydrographs (-0.52±0.30 km3/yr) is within the range of satellite-derived estimates (-0.44 to -2.04 km3/yr) that result from uncertainty associated with ΔSMS (CLM, NOAH, VIC) and GRACE data processing techniques. Recent (2003 to 2007) estimates of groundwater depletion are substantially greater than the long-term (1985 to 2007) mean (-0.21±0.03 km3/yr) and are explained primarily by substantial increases in groundwater abstraction for the dry-season irrigation and drinking water supplies over the last two decades.

Monitoring groundwater storage change in Mekong Delta using Gravity Recovery and Climate Experiment (GRACE) data

NASA Astrophysics Data System (ADS)

Aierken, A.; Lee, H.; Hossain, F.; Bui, D. D.; Nguyen, L. D.

2016-12-01

The Mekong Delta, home to almost 20 million inhabitants, is considered one of the most important region for Vietnam as it is the agricultural and industrial production base of the nation. However, in recent decades, the region is seriously threatened by variety of environmental hazards, such as floods, saline water intrusion, arsenic contamination, and land subsidence, which raise its vulnerability to sea level rise due to global climate change. All these hazards are related to groundwater depletion, which is the result of dramatically increased over-exploitation. Therefore, monitoring groundwater is critical to sustainable development and most importantly, to people's life in the region. In most countries, groundwater is monitored using well observations. However, because of its spatial and temporal gaps and cost, it is typically difficult to obtain large scale, continuous observations. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry mission has delivered freely available Earth's gravity variation data, which can be used to obtain terrestrial water storage (TWS) changes. In this study, the TWS anomalies over the Mekong Delta, which are the integrated sum of anomalies of soil moisture storage (SMS), surface water storage (SWS), canopy water storage (CWS), groundwater storage (GWS), have been obtained using GRACE CSR RL05 data. The leakage error occurred due to GRACE signal processing has been corrected using several different approaches. The groundwater storage anomalies were then derived from TWS anomalies by removing SMS, and CWS anomalies simulated by the four land surface models (NOAH, CLM, VIC and MOSAIC) in the Global Land Data Assimilation System (GLDAS), as well as SWS anomalies estimated using ENVISAT satellite altimetry and MODIS imagery. Then, the optimal GRACE signal restoration method for the Mekong Delta is determined with available in-situ well data. The estimated GWS anomalies revealed continuously decreasing trend, and the flood and drought occurred in 2004 and 2012, respectively. Our study reveals the ability of GRACE to monitor groundwater depletion as well as flood and drought in regional scale.

Comparison of Seasonal Terrestrial Water Storage Variations from GRACE with Groundwater-level Measurements from the High Plains Aquifer (USA)

NASA Technical Reports Server (NTRS)

Strassberg, Gil; Scanlon, Bridget R.; Rodell, Matthew

2007-01-01

This study presents the first direct comparison of variations in seasonal GWS derived from GRACE TWS and simulated SM with GW-level measurements in a semiarid region. Results showed that variations in GWS and SM are the main sources controlling TWS changes over the High Plains, with negligible storage changes from surface water, snow, and biomass. Seasonal variations in GRACE TWS compare favorably with combined GWS from GW-level measurements (total 2,700 wells, average 1,050 GW-level measurements per season) and simulated SM from the Noah land surface model (R = 0.82, RMSD = 33 mm). Estimated uncertainty in seasonal GRACE-derived TWS is 8 mm, and estimated uncertainty in TWS changes is 11 mm. Estimated uncertainty in SM changes is 11 mm and combined uncertainty for TWS-SM changes is 15 mm. Seasonal TWS changes are detectable in 7 out of 9 monitored periods and maximum changes within a year (e.g. between winter and summer) are detectable in all 5 monitored periods. Grace-derived GWS calculated from TWS-SM generally agrees with estimates based on GW-level measurements (R = 0.58, RMSD = 33 mm). Seasonal TWS-SM changes are detectable in 5 out of the 9 monitored periods and maximum changes are detectable in all 5 monitored periods. Good correspondence between GRACE data and GW-level measurements from the intensively monitored High Plains aquifer validates the potential for using GRACE TWS and simulated SM to monitor GWS changes and aquifer depletion in semiarid regions subjected to intensive irrigation pumpage. This method can be used to monitor regions where large-scale aquifer depletion is ongoing, and in situ measurements are limited, such as the North China Plain or western India. This potential should be enhanced by future advances in GRACE processing, which will improve the spatial and temporal resolution of TWS changes, and will further increase applicability of GRACE data for monitoring GWS.

The Natural Law of Strategy: A Contrarian’s Lament

DTIC Science & Technology

2011-08-26

DHS, to produce strategy on ever conceivable necessity or non-necessity. There is a Noah ‟ s Ark of hes and shes, two by two, strategies. The...A Contrarian’s Lament 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) National Defense University,Near East and South Asia Center for Strategic Studies,2100

Ohio River Environmental Assessment Cultural Resources Reconnaissance Technical Report for the State of Kentucky Portion,

DTIC Science & Technology

1977-09-15

and maps. Informtion was acquired, where possible, by letter which included a list of involved counties. This letter was sent to those individua s or...approximate extent of site along N- S axis in meters; the second the approximate extent of site along E-W axis. AMSL in Meters Records the elevation...America from Asia via the Bering Strait, originating from the descendants of Noah . (Other than this, Atwater was a methodical and accurate surveyor

Micro-PROUST.

DTIC Science & Technology

1985-06-01

Noah needs to keep track of rainfall in the New Haven area in order to determine when to launch his ark . Write a...UNLSIIDFG92 N 2.. II4II 111220 11111 11J.4 MICROCOPY RESOLUTION TEST CHART S "- )ARDS 1963 A S !!? Ii~ Sii ". . . ," .’ "" o o." .* -. ° . ". * -. * " . -- I...unflagging effort and support in seeing this project through to fruition. V 7 .. ° - . . - , .-. - . - ., S .-’ S 1. ES , " , - u < . i ’ - SiCU,r7

Improved Manufacturing Methods for Navy Peacoats

DTIC Science & Technology

1991-09-30

oaeration requir= S a heavy ;;erd, feed machine II n CC T is can e done either with a r I 2 .’" ark buttonhoie loc-tion with the I Ir fo I...AD-A243 702 F A S H I 0 N I INSTITUTE OF TECHNOLOGYI R E S EARCH DTIC I REPORT SELECTEI.. D D I IMPROVED MANUFACTURING METHODS FOR NAVY PEACOATS I I...A008. I IHenr A/Seesselberg Dir ctor, Advanced Apparel Manufacturing Technology Programs, Fashion Institute of Technology I Noah Bronner Research

Devils in the Dialogue: The Air Force and Congress

DTIC Science & Technology

2011-06-01

the United States, Article I, Section 8. 111th Cong., 1st sess., 2009, S . Doc 111-4. 118 John Haskell, Congress in Context (Philadelphia, PA...Congress. 12 January 2005. http://digital.library.unt.edu/ ark :/67531/metacrs7624/m1/1/high_res_d/98- 558_2005Jan12.pdf 141 HR 91-1570, FY71 DOD...February 2011 260 Shachtman, Noah . ―Pentagon Chief Rips Heart Out of Army‘s ‗Future‘,‖ Wired, 6 April 2009, http://www.wired.com/dangerroom/2009/04

Regulations of irrigation on regional climate in the Heihe watershed, China, and its implications to water budget

NASA Astrophysics Data System (ADS)

Zhang, X.

2015-12-01

In the arid area, such as the Heihe watershed in Northwest China, agriculture is heavily dependent on the irrigation. Irrigation suggests human-induced hydro process, which modifies the local climate and water budget. In this study, we simulated the irrigation-induced changes in surface energy/moisture budgets and modifications on regional climate, using the WRF-NoahMP modle with an irrigation scheme. The irrigation scheme was implemented following the roles that soil moisture is assigned a saturated value once the mean soil moisture of all root layers is lower than 70% of fileld capacity. Across the growth season refering from May to September, the simulated mean irrigation amount of the 1181 cropland gridcells is ~900 mm, wihch is close to the field measurments of around 1000 mm. Such an irrigation largely modified the surface energy budget. Due to irrigation, the surface net solar radiation increased by ~76.7 MJ (~11 Wm-2) accouting for ~2.3%, surface latent and senbile heat flux increased by 97.7 Wm-2 and decreased by ~79.7 Wm-2 respectively; and local daily mean surface air temperature was thereby cooling by ~1.1°C. Corresponding to the surface energy changes, wind and circulation were also modified and regional water budget is therefore regulated. The total rainfall in the irrigation area increased due to more moisture from surface. However, the increased rainfall is only ~6.5mm (accounting for ~5% of background rainfall) which is much less than the increased evaporation of ~521.5mm from surface. The ~515mm of water accounting for 57% of total irrigation was transported outward by wind. The other ~385 mm accounting for 43% of total irrigation was transformed to be runoff and soil water. These results suggest that in the Heihe watershed irrigation largely modify local energy budget and cooling surface. This study also implicate that the existing irrigation may waste a large number of water. It is thereby valuable to develope effective irrigation scheme to save water resources.

Ensemble Simulation of Sierra Nevada Snowmelt Runoff Using a Regional Climate Modeling Approach

NASA Astrophysics Data System (ADS)

Holtzman, N.; Pavelsky, T.; Wrzesien, M.

2017-12-01

The snowmelt-dominated watersheds on the western slopes of the California Sierra Nevada drain into reservoirs that generate electricity and help irrigate Central Valley farms. At the end of the wet season of each year, around April 1, most of the water that will become runoff in these basins is stored as snow at high elevations. Snow measurements provide a good estimate of the total annual runoff to come. For efficient water management, however, it is also useful to know the timing of runoff. When and how large will the peak flow into a reservoir be, and how fast will the flow decline after it peaks? We address such questions using a coupled regional climate and land surface model, WRF and Noah-MP, to dynamically downscale the North American Regional Reanalysis (NARR) with an ensemble approach. First, we assess several methods of deriving melt-season runoff from WRF. We run WRF for a complete water year, and also test initializing WRF snow from observation-based datasets at the approximate date of peak snow water equivalent. By aggregating the modeled runoffs over the drainage basins of reservoirs and comparing to naturalized flow data, we can assess the basin-scale snow accumulation accuracy of WRF and the other datasets in the Sierra. After choosing a procedure to set the model snow at the end of the wet season, we apply in WRF the melt-season meteorology from 20 different past years of NARR to produce an ensemble of simulations, each with modeled flows into 8 reservoirs spanning the Sierra. We use the ensemble to characterize the likely spread in the timing and magnitude of hydrologic outcomes during the melt season. Probabilistic forecasts can help water-energy systems operate more efficiently. The ensemble also shows the effect of warm-season temperature extremes on flow timing, allowing human systems to prepare for those possibilities. Finally, the ensemble provides a baseline estimate of the maximum variability in runoff timing that could be generated by past conditions. If future runoff patterns consistently exceed the extremes found in the ensemble, nonstationary hydroclimate can be inferred.

An inter-model comparison of urban canopy effects on climate

NASA Astrophysics Data System (ADS)

Halenka, Tomas; Karlicky, Jan; Huszar, Peter; Belda, Michal; Bardachova, Tatsiana

2017-04-01

The role of cities is increasing and will continue to increase in future, as the population within the urban areas is growing faster, with the estimate for Europe of about 84% living in urban areas in about mid of 21st century. To assess the impact of cities and, in general, urban surfaces on climate, using of modeling approach is well appropriate. Moreover, with higher resolution, urban areas becomes to be better resolved in the regional models and their relatively significant impacts should not be neglected. Model descriptions of urban canopy related meteorological effects can, however, differ largely given the odds in the driving models, the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. In this study we try to contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two driving models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Actually, in RegCM4 we used our implementation of the Single Layer Urban Canopy Model (SLUCM) in BATS scheme and CLM4.5 option with urban parameterization based on SLUCM concept as well, in WRF we used all the three options, i.e. bulk, SLUCM and more complex and sophisticated Building Environment Parameterization (BEP) connected with Building Energy Model (BEM). As a reference simulations, runs with no urban areas and with no urban parameterizations were performed. Effects of cities on urban and rural areas were evaluated. Effect of reducing diurnal temperature range in cities (around 2 °C in summer) is noticeable in all simulation, independent to urban parameterization type and model. Also well-known warmer summer city nights appear in all simulations. Further, winter boundary layer increase by 100-200 m, together with wind reduction, is visible in all simulations. The spatial distribution of the night-time temperature response of models to urban canopy forcing is rather similar in each set-up, showing temperature increases up to 3°C in summer. In general, much lower increase are modeled for day-time conditions, which can be even slightly negative due to dominance of shadowing in urban canyons, especially in the morning hours. The winter temperature response, driven mainly by anthropogenic heat (AH) is strong in urban schemes where the building-street energy exchange is more resolved and is smaller, where AH is simply prescribed as additive flux to the sensible heat. Somewhat larger differences between the models are encountered for the response of wind and the height of planetary boundary layer (ZPBL), with dominant increases from a few 10 m up to 250 m depending on the model. The comparison of observation of diurnal temperature amplitude from ECAD data with model results and hourly data from Prague with model hourly values show improvement when urban effects are considered. Larger spread encountered for wind and turbulence (as ZPBL) should be considered when choices of urban canopy schemes are made, especially in connection with modeling transport of pollutants within/from cities. Another conclusion is that choosing more complex urban schemes does not necessary improves model performance and using simpler and computationally less demanding (e.g. single layer) urban schemes, is often sufficient.

Treatment of air pollution control residues with iron rich waste sulfuric acid: does it work for antimony (Sb)?

PubMed

Okkenhaug, Gudny; Breedveld, Gijs D; Kirkeng, Terje; Lægreid, Marit; Mæhlum, Trond; Mulder, Jan

2013-03-15

Antimony (Sb) in air pollution control (APC) residues from municipal solid waste incineration has gained increased focus due to strict Sb leaching limits set by the EU landfill directive. Here we study the chemical speciation and solubility of Sb at the APC treatment facility NOAH Langøya (Norway), where iron (Fe)-rich sulfuric acid (∼3.6M, 2.3% Fe(II)), a waste product from the industrial extraction of ilmenite, is used for neutralization. Antimony in water extracts of untreated APC residues occurred exclusively as pentavalent antimonate, even at low pH and Eh values. The Sb solubility increased substantially at pH<10, possibly due to the dissolution of ettringite (at alkaline pH) or calcium (Ca)-antimonate. Treated APC residues, stored anoxically in the laboratory, simulating the conditions at the NOAH Langøya landfill, gave rise to decreasing concentrations of Sb in porewater, occurring exclusively as Sb(V). Concentrations of Sb decreased from 87-918μgL(-1) (day 3) to 18-69μgL(-1) (day 600). We hypothesize that an initial sorption of Sb to Fe(II)-Fe(III) hydroxides (green rust) and eventually precipitation of Ca- and Fe-antimonates (tripuhyite; FeSbO4) occurred. We conclude that Fe-rich, sulfuric acid waste is efficient to immobilize Sb in APC residues from waste incineration. Copyright © 2013 Elsevier B.V. All rights reserved.

Nationwide Operational Assessment of Hazards and success stories in disaster prevention and mitigation in the Philippines

NASA Astrophysics Data System (ADS)

Mahar Francisco Lagmay, Alfredo

2016-04-01

The Philippines, being a locus of typhoons, tsunamis, earthquakes, and volcanic eruptions, is a hotbed of disasters. Natural hazards inflict loss of lives and costly damage to property in the country. In 2011, after tropical storm Washi devastated cities in southern Philippines, the Department of Science and Technology put in place a responsive program to warn and give communities hours-in-advance lead-time to prepare for imminent hazards and use advanced science and technology to enhance geohazard maps for more effective disaster prevention and mitigation. Since its launch, there have been many success stories on the use of Project NOAH, which after Typhoon Haiyan was integrated into the Pre-Disaster Risk Assessment (PDRA) system of the National Disaster Risk Reduction and Management Council (NDRRMC), the government agency tasked to prepare for, and respond to, natural calamities. Learning from past disasters, NDRRMC now issues warnings, through scientific advise from DOST-Project NOAH and PAGASA (Philippine Weather Bureau) that are hazards-specific, area-focused and time-bound. Severe weather events in 2015 generated dangerous hazard phenomena such as widespread floods and massive debris flows, which if not for timely, accessible and understandable warnings, could have turned into disasters. We call these events as "disasters that did not happen". The innovative warning system of the Philippine government has so far proven effective in addressing the impacts of hydrometeorological hazards and can be employed elsewhere in the world.

The impact of the uncertainty in the initial soil moisture condition of irrigated areas on the spatiotemporal characteristics of convective activity in Central Greece

NASA Astrophysics Data System (ADS)

Kotsopoulos, Stylianos; Ioannis, Tegoulias; Ioannis, Pytharoulis; Stergios, Kartsios; Dimitrios, Bampzelis; Theodore, Karacostas

2015-04-01

The region of Thessaly is the second largest plain in Greece and has a vital role in the financial life of the country, because of its significant agricultural production. The intensive and extensive cultivation of irrigated crops, in combination with the population increase and the alteration of precipitation patterns due to climate change, often leading the region to experience severe drought conditions, especially during the warm period of the year. The aim of the DAPHNE project is to tackle the problem of drought in this area by means of Weather Modification.In the framework of the project DAPHNE, the numerical weather prediction model WRF-ARW 3.5.1 is used to provide operational forecasts and hindcasts for the region of Thessaly. The goal of this study is to investigate the impact of the uncertainty in the initial soil moisture condition of irrigated areas, on the spatiotemporal characteristics of convective activity in the region of interest. To this end, six cases under the six most frequent synoptic conditions, which are associated with convective activity in the region of interest, are utilized, considering six different soil moisture initialization scenarios. In the first scenario (Control Run), the model is initialized with the surface soil moisture of the ECMWF analysis data, that usually does not take into account the modification of soil moisture due to agricultural activity in the area of interest. In the other five scenarios (Experiment 1,2,3,4,5) the soil moisture in the upper soil layers of the study area are modified from -50% to 50% of field capacity (-50%FC, -25%FC, FC, 25%FC, 50%FC),for the irrigated cropland.Three model domains, covering Europe, the Mediterranean Sea and northern Africa (d01), the wider area of Greece (d02) and central Greece - Thessaly region (d03) are used at horizontal grid-spacings of 15km, 5km and 1km respectively. ECMWF operational analyses at 6-hourly intervals (0.25ox0.25o lat.-long.) are imported as initial and boundary conditions of the coarse domain, while in the vertical, all nests employ 39 sigma levels (up to 50 hPa) with increased resolution in the boundary layer. Microphysical processes are represented by WSM6 scheme, sub-grid scale convection by Kain-Fritsch scheme, longwave and shortwave radiation by RRTMG scheme, surface layer by Monin-Obukhov (MM5), boundary layer by Yonsei University and soil surface scheme by NOAH Unified model. The model numerical results are evaluated against surface precipitation data and data obtained using a C-band (5cm) weather radar located in the centre of the innermost domain. Acknowledgements: This research is co-financed by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" (contract number 11SYN_8_1088 - DAPHNE) in the framework of the operational programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-2013).

Logical steps to moon, Mars and beyond

NASA Astrophysics Data System (ADS)

Kuriki, Kyoichi

1993-10-01

A scenario of the space activities aimed at exploration of moon, Mars, and other planets is proposed. The scenario uses motivations based on the fundamental human instinct, i.e. intellectual curiosity and survival of the humankind. It is shown how these key drivers are threading through the known programs including Space Shuttle and Space Station, Space Energy Exploitation and Space Factory, Lunar Base, and Mars Base. It is concluded that an eventual goal of the mission from planet earth is to set Noah's Arc off into space in the next millenium.

The Emergency Alternative Arrangement Exception to the National Environmental Policy Act: What Constitutes an Emergency? Should the Navy Pin Its Hopes on Noah Webster?

DTIC Science & Technology

2009-08-31

granted for discharging pumped water into Lake Pontchartrain without a NPDES permit under the CW A, for depositing into wetlands without a CW A 404...484. 116 32 c.F.R. § 989.34(b) (2009). 1171d. 118 Colonel E.G. Willard, Lieutenant Colonel Tom Zimmerman, and Lieutenant Colonel Eric Bee ...Service in December 1985 issued a permit authorizing the capture and removal of all six surviving wild California condors. 177 This was a change in their

Hydrological excitation of polar motion by different variables of the GLDAS models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.

The relative contribution of the precipitation and evapotranspiration on total terrestrial water storage change

NASA Astrophysics Data System (ADS)

Zhang, Y.

2017-12-01

Changes of global terrestrial water storage (TWS) retrieved from the Gravity Recovery and Climate Experiment (GRACE) satellite mission has been extensively evaluated by previous studies. However, attributions of global TWS changes are still poorly understood. In this study, the responses TWS to two most important surface water fluxes, precipitation (P) and evapotranspiration (ET), were comprehensively examined based on 3 global P datasets and 3 global ET datasets. In addition, the relative contribution of P and ET to TWS changes were quantified using the hierarchical partitioning analysis. Results show that, over the period of Apr. 2002 to July. 2016, more than 40.5% global continent experienced significant TWS decrease, while significant TWS increases were observed over 36% of global continent. A general positive effect of P on TWS was observed over almost all land, but a contrasting response of TWS to ET were identified between arid or cold areas and humid areas with positive and negative TWS-ET relationship, respectively. Global as a whole, precipitation from GPCC and ET simulated by the Noah model forcing by Global land Data Assimilation System (GLDAS) has the highest performance in explaining global TWS change. HP analysis suggests that the independent contribution of ET to TWS change is apparently higher than that of P. Furthermore, with the decrease of climate humidity, the contribution of P is decreasing, while the contribution of ET is increasing. Spatially speaking, ET has higher impacts on TWS than P in arid areas, while the opposite function was identified for very humid and cold areas. Knowledge from this study is crucial for the understanding of the response of global TWS change to climate change.

Accuracy of Snow Water Equivalent Estimated From GPS Vertical Displacements: A Synthetic Loading Case Study for Western U.S. Mountains

NASA Astrophysics Data System (ADS)

Enzminger, Thomas L.; Small, Eric E.; Borsa, Adrian A.

2018-01-01

GPS monitoring of solid Earth deformation due to surface loading is an independent approach for estimating seasonal changes in terrestrial water storage (TWS). In western United States (WUSA) mountain ranges, snow water equivalent (SWE) is the dominant component of TWS and an essential water resource. While several studies have estimated SWE from GPS-measured vertical displacements, the error associated with this method remains poorly constrained. We examine the accuracy of SWE estimated from synthetic displacements at 1,395 continuous GPS station locations in the WUSA. Displacement at each station is calculated from the predicted elastic response to variations in SWE from SNODAS and soil moisture from the NLDAS-2 Noah model. We invert synthetic displacements for TWS, showing that both seasonal accumulation and melt as well as year-to-year fluctuations in peak SWE can be estimated from data recorded by the existing GPS network. Because we impose a smoothness constraint in the inversion, recovered TWS exhibits mass leakage from mountain ranges to surrounding areas. This leakage bias is removed via linear rescaling in which the magnitude of the gain factor depends on station distribution and TWS anomaly patterns. The synthetic GPS-derived estimates reproduce approximately half of the spatial variability (unbiased root mean square error ˜50%) of TWS loading within mountain ranges, a considerable improvement over GRACE. The inclusion of additional simulated GPS stations improves representation of spatial variations. GPS data can be used to estimate mountain-range-scale SWE, but effects of soil moisture and other TWS components must first be subtracted from the GPS-derived load estimates.

Mammalian Collection on Noah's Ark: The Effects of Beauty, Brain and Body Size

PubMed Central

Frynta, Daniel; Šimková, Olga; Lišková, Silvie; Landová, Eva

2013-01-01

The importance of today's zoological gardens as the so-called “Noah's Ark” grows as the natural habitat of many species quickly diminishes. Their potential to shelter a large amount of individuals from many species gives us the opportunity to reintroduce a species that disappeared in nature. However, the selection of animals to be kept in zoos worldwide is highly selective and depends on human decisions driven by both ecological criteria such as population size or vulnerability and audience-driven criteria such as aesthetic preferences. Thus we focused our study on the most commonly kept and bred animal class, the mammals, and we asked which factors affect various aspects of the mammalian collection of zoos. We analyzed the presence/absence, population size, and frequency per species of each of the 123 mammalian families kept in the worldwide zoo collection. Our aim was to explain these data using the human-perceived attractiveness of mammalian families, their body weight, relative brain size and species richness of the family. In agreement with various previous studies, we found that the body size and the attractiveness of mammals significantly affect all studied components of the mammalian collection of zoos. There is a higher probability of the large and attractive families to be kept. Once kept, these animals are presented in larger numbers in more zoos. On the contrary, the relative mean brain size only affects the primary selection whether to keep the family or not. It does not affect the zoo population size or the number of zoos that keep the family. PMID:23690985

Mammalian collection on Noah's Ark: the effects of beauty, brain and body size.

PubMed

Frynta, Daniel; Šimková, Olga; Lišková, Silvie; Landová, Eva

2013-01-01

The importance of today's zoological gardens as the so-called "Noah's Ark" grows as the natural habitat of many species quickly diminishes. Their potential to shelter a large amount of individuals from many species gives us the opportunity to reintroduce a species that disappeared in nature. However, the selection of animals to be kept in zoos worldwide is highly selective and depends on human decisions driven by both ecological criteria such as population size or vulnerability and audience-driven criteria such as aesthetic preferences. Thus we focused our study on the most commonly kept and bred animal class, the mammals, and we asked which factors affect various aspects of the mammalian collection of zoos. We analyzed the presence/absence, population size, and frequency per species of each of the 123 mammalian families kept in the worldwide zoo collection. Our aim was to explain these data using the human-perceived attractiveness of mammalian families, their body weight, relative brain size and species richness of the family. In agreement with various previous studies, we found that the body size and the attractiveness of mammals significantly affect all studied components of the mammalian collection of zoos. There is a higher probability of the large and attractive families to be kept. Once kept, these animals are presented in larger numbers in more zoos. On the contrary, the relative mean brain size only affects the primary selection whether to keep the family or not. It does not affect the zoo population size or the number of zoos that keep the family.

The role of organic soil layer on the fate of Siberian larch forest and near-surface permafrost under changing climate: A simulation study

NASA Astrophysics Data System (ADS)

SATO, H.; Iwahana, G.; Ohta, T.

2013-12-01

Siberian larch forest is the largest coniferous forest region in the world. In this vast region, larch often forms nearly pure stands, regenerated by recurrent fire. This region is characterized by a short and dry growing season; the annual mean precipitation for Yakutsk was only about 240 mm. To maintain forest ecosystem under such small precipitation, underlying permafrost and seasonal soil freezing-thawing-cycle have been supposed to play important roles; (1) frozen ground inhibits percolation of soil water into deep soil layers, and (2) excess soil water at the end of growing season can be carried over until the next growing season as ice, and larch trees can use the melt water. As a proof for this explanation, geographical distribution of Siberian larch region highly coincides with continuous and discontinuous permafrost zone. Recent observations and simulation studies suggests that existences of larch forest and permafrost in subsurface layer are co-dependent; permafrost maintains the larch forest by enhancing water use efficiency of trees, while larch forest maintains permafrost by inhibiting solar radiation and preventing heat exchanges between soil and atmosphere. Owing to such complexity and absence of enough ecosystem data available, current-generation Earth System Models significantly diverse in their prediction of structure and key ecosystem functions in Siberian larch forest under changing climate. Such uncertainty should in turn expand uncertainty over predictions of climate, because Siberian larch forest should have major role in the global carbon balance with its huge area and vast potential carbon pool within the biomass and soil, and changes in boreal forest albedo can have a considerable effect on Northern Hemisphere climate. In this study, we developed an integrated ecosystem model, which treats interactions between plant-dynamics and freeze-thaw cycles. This integrated model contains a dynamic global vegetation model SEIB-DGVM, which simulates plant and carbon dynamics. It also contains a one-dimensional land surface model NOAH 2.7.1, which simulates soil moisture (both liquid and frozen), soil temperature, snowpack depth and density, canopy water content, and the energy and water fluxes. This integrated model quantitatively reconstructs post-fire development of forest structure (i.e. LAI and biomass) and organic soil layer, which dampens heat exchanges between soil and atmosphere. With the post-fire development of LAI and the soil organic layer, the integrated model also quantitatively reconstructs changes in seasonal maximum of active layer depth. The integrated model is then driven by the IPCC A1B scenario of rising atmospheric CO2, and by climate changes during the twenty-first century resulting from the change in CO2. This simulation suggests that forecasted global warming would causes decay of Siberian larch ecosystem, but such responses could be delayed by "memory effect" of the soil organic layer for hundreds of years.

At least Noah had some warning

NASA Astrophysics Data System (ADS)

Duffield, Wendell A.

Tlachoc was worried. Life had never been easy in the mountainous jungle of this area that much later would be called Chiapas, in the southern part of what is now Mexico. But recently even the simplest of daily chores came with an unusual amount of stress and failure. During the past complete cycle of the seasons, the wild animals that were sources of meat, clothing, and bone tools had become increasingly skittish. For no apparent reason, these creatures now behaved as though an added sense helped them avoid close encounters with hunters, as though some foreign and disturbing sensation kept them fully alert.

An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015

NASA Astrophysics Data System (ADS)

Hunt, E. D.; Otkin, J.; Zhong, Y.

2017-12-01

Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.

Application of NARR-based NLDAS Ensemble Simulations to Continental-Scale Drought Monitoring

NASA Astrophysics Data System (ADS)

Alonge, C. J.; Cosgrove, B. A.

2008-05-01

Government estimates indicate that droughts cause billions of dollars of damage to agricultural interests each year. More effective identification of droughts would directly benefit decision makers, and would allow for the more efficient allocation of resources that might mitigate the event. Land data assimilation systems, with their high quality representations of soil moisture, present an ideal platform for drought monitoring, and offer many advantages over traditional modeling systems. The recently released North American Regional Reanalysis (NARR) covers the NLDAS domain and provides all fields necessary to force the NLDAS for 27 years. This presents an ideal opportunity to combine NARR and NLDAS resources into an effective real-time drought monitor. Toward this end, our project seeks to validate and explore the NARR's suitability as a base for drought monitoring applications - both in terms of data set length and accuracy. Along the same lines, the project will examine the impact of the use of different (longer) LDAS model climatologies on drought monitoring, and will explore the advantages of ensemble simulations versus single model simulations in drought monitoring activities. We also plan to produce a NARR- and observation-based high quality 27 year, 1/8th degree, 3-hourly, land surface and meteorological forcing data sets. An investigation of the best way to force an LDAS-type system will also be made, with traditional NLDAS and NLDASE forcing options explored. This presentation will focus on an overview of the drought monitoring project, and will include a summary of recent progress. Developments include the generation of forcing data sets, ensemble LSM output, and production of model-based drought indices over the entire NLDAS domain. Project forcing files use 32km NARR model output as a data backbone, and include observed precipitation (blended CPC gauge, PRISM gauge, Stage II, HPD, and CMORPH) and a GOES-based bias correction of downward solar radiation. Multiple LSM simulations have been conducted using the Noah, Mosaic, CLM3, HYSSiB, and Catchment LSMs. These simulations, along with the NARR-based forcing data form the basis for several drought indices. These include standard measures such as the Palmer-type indices, LDAS-type percentile and anomaly values, and CLM3-based vegetation condition index values.

Regional Climate Modeling over the Marmara Region, Turkey, with Improved Land Cover Data

NASA Astrophysics Data System (ADS)

Sertel, E.; Robock, A.

2007-12-01

Land surface controls the partitioning of available energy at the surface between sensible and latent heat,and controls partitioning of available water between evaporation and runoff. Current land cover data available within the regional climate models such as Regional Atmospheric Modeling System (RAMS), the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) was obtained from 1- km Advanced Very High Resolution Radiometer satellite images spanning April 1992 through March 1993 with an unsupervised classification technique. These data are not up-to-date and are not accurate for all regions and some land cover types such as urban areas. Here we introduce new, up-to-date and accurate land cover data for the Marmara Region, Turkey derived from Landsat Enhanced Thematic Mapper images into the WRF regional climate model. We used several image processing techniques to create accurate land cover data from Landsat images obtained between 2001 and 2005. First, all images were atmospherically and radiometrically corrected to minimize contamination effects of atmospheric particles and systematic errors. Then, geometric correction was performed for each image to eliminate geometric distortions and define images in a common coordinate system. Finally, unsupervised and supervised classification techniques were utilized to form the most accurate land cover data yet for the study area. Accuracy assessments of the classifications were performed using error matrix and kappa statistics to find the best classification results. Maximum likelihood classification method gave the most accurate results over the study area. We compared the new land cover data with the default WRF land cover data. WRF land cover data cannot represent urban areas in the cities of Istanbul, Izmit, and Bursa. As an example, both original satellite images and new land cover data showed the expansion of urban areas into the Istanbul metropolitan area, but in the WRF land cover data only a limited area along the Bosporus is shown as urban. In addition, the new land cover data indicate that the northern part of Istanbul is covered by evergreen and deciduous forest (verified by ground truth data), but the WRF data indicate that most of this region is croplands. In the northern part of the Marmara Region, there is bare ground as a result of open mining activities and this class can be identified in our land cover data, whereas the WRF data indicated this region as woodland. We then used this new data set to conduct WRF simulations for one main and two nested domains, where the inner-most domain represents the Marmara Region with 3 km horizontal resolution. The vertical domain of both main and nested domains extends over 28 vertical levels. Initial and boundary conditions were obtained from National Centers for Environmental Prediction-Department of Energy Reanalysis II and the Noah model was selected as the land surface model. Two model simulations were conducted; one with available land cover data and one with the newly created land cover data. Using detailed meteorological station data within the study area, we find that the simulation with the new land cover data set produces better temperature and precipitation simulations for the region, showing the value of accurate land cover data and that changing land cover data can be an important influence on local climate change.

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

PubMed Central

Scanlon, Bridget R.; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y.; van Beek, Ludovicus P. H.; Wiese, David N.; Reedy, Robert C.; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F. P.

2018-01-01

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. PMID:29358394

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data.

PubMed

Scanlon, Bridget R; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y; Müller Schmied, Hannes; van Beek, Ludovicus P H; Wiese, David N; Wada, Yoshihide; Long, Di; Reedy, Robert C; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F P

2018-02-06

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤-0.5 km 3 /y) and increasing (≥0.5 km 3 /y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km 3 /y, whereas most models estimate decreasing trends (-71 to 11 km 3 /y). Land water storage trends, summed over all basins, are positive for GRACE (∼71-82 km 3 /y) but negative for models (-450 to -12 km 3 /y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. Copyright © 2018 the Author(s). Published by PNAS.

A Multiphysics and Multiscale Software Environment for Modeling Astrophysical Systems

NASA Astrophysics Data System (ADS)

Portegies Zwart, Simon; McMillan, Steve; O'Nualláin, Breanndán; Heggie, Douglas; Lombardi, James; Hut, Piet; Banerjee, Sambaran; Belkus, Houria; Fragos, Tassos; Fregeau, John; Fuji, Michiko; Gaburov, Evghenii; Glebbeek, Evert; Groen, Derek; Harfst, Stefan; Izzard, Rob; Jurić, Mario; Justham, Stephen; Teuben, Peter; van Bever, Joris; Yaron, Ofer; Zemp, Marcel

We present MUSE, a software framework for tying together existing computational tools for different astrophysical domains into a single multiphysics, multiscale workload. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for a generalized stellar systems workload. MUSE has now reached a "Noah's Ark" milestone, with two available numerical solvers for each domain. MUSE can treat small stellar associations, galaxies and everything in between, including planetary systems, dense stellar clusters and galactic nuclei. Here we demonstrate an examples calculated with MUSE: the merger of two galaxies. In addition we demonstrate the working of MUSE on a distributed computer. The current MUSE code base is publicly available as open source at http://muse.li.

Enhancements to the WRF-Hydro Hydrologic Model Structure for Semi-arid Environments

NASA Astrophysics Data System (ADS)

Lahmers, T. M.; Gupta, H.; Hazenberg, P.; Castro, C. L.; Gochis, D.; Yates, D. N.; Dugger, A. L.; Goodrich, D. C.

2017-12-01

The NOAA National Water Center (NWC) implemented an operational National Water Model (NWM) in August 2016 to simulate and forecast streamflow and soil moisture throughout the Contiguous US (CONUS). The NWM is based on the WRF-Hydro hydrologic model architecture, with a 1-km resolution Noah-MP LSM grid and a 250m routing grid. The operational NWM does not currently resolve infiltration of water from the beds of ephemeral channels, which is an important component of the water balance in semi-arid environments common in many portions of the western US. This work demonstrates the benefit of a conceptual channel infiltration function in the WRF-Hydro model architecture following calibration. The updated model structure and parameters for the NWM architecture, when implemented operationally, will permit its use in flow simulation and forecasting in the southwest US, particularly for flash floods in basins with smaller drainage areas. Our channel infiltration function is based on that of the KINEROS2 semi-distributed hydrologic model, which has been tested throughout the southwest CONUS for flash flood forecasts. Model calibration utilizes the Dynamically Dimensioned Search (DDS) algorithm, and the model is calibrated using NLDAS-2 atmospheric forcing and NCEP Stage-IV precipitation. Our results show that adding channel infiltration to WRF-Hydro can produce a physically consistent hydrologic response with a high-resolution gauge based precipitation forcing dataset in the USDA-ARS Walnut Gulch Experimental Watershed. NWM WRF-Hydro is also tested for the Babocomari River, Beaver Creek, and Sycamore Creek catchments in southern and central Arizona. In these basins, model skill is degraded due to uncertainties in the NCEP Stage-IV precipitation forcing dataset.

Secular and annual hydrologic effects from the Plate Boundary Observatory GPS network

NASA Astrophysics Data System (ADS)

Meertens, C. M.; Wahr, J. M.; Borsa, A. A.; Jackson, M. E.; Herring, T.

2009-12-01

The Plate Boundary Observatory (PBO) GPS network is providing accurate and spatially coherent vertical signals that can be interpreted in terms of hydrological loading and poroelastic effects from both natural and anthropogenic changes in water storage. Data used for this analysis are the precise coordinate time series produced on a daily basis by PBO Analysis Centers at New Mexico Institute of Mining and Technology and at Central Washington University and combined by the Analysis Center Coordinator at the Massachusetts Institute of Technology. These products, as well as derived velocity solutions, are made freely available from the UNAVCO Data Center in Boulder. Analysis of secular trends and annual variations in the time series was made using the analysis software of Langbein, 2008. Spatial variations in the amplitude and phase of the annual vertical component of motion allow for identification of anthropogenic effects due to water pumping, irrigation, and reservoir lake variations, and of outliers due to instrumental or other local site effects. Vertical annual signals of 8-10 mm peak-to-peak amplitude are evident at stations in the mountains of northern and central California and the Pacific Northwest. The peak annual uplift is in October and is correlated to hydrological loading effects. Mountainous areas appear to be responding elastically to the load of the water contained in surface soil, fractures, and snow. Vertical signals are highest when the water load is at a minimum. The vertical elastic hydrologic loading signal was modeled using the 0.25 degree community NOAH land-surface model (LSM) and generally fits the observed GPS signal. Addition comparisons will be made using the Mosaic LSM and the NOAA “Leaky Bucket” hydrologic model. In contrast to mountain stations that are installed principally in bedrock, stations in the valleys of California are installed in sediments. Observations from these stations show greater spatial variability ranging from almost no detectable annual signal to very large, 20-30 mm, vertical amplitudes that reach a maximum in March. Vertical signals in the valleys are the result of poroelastic effects induced by groundwater variations caused by pumping for irrigation or other purposes and are highest when groundwater is at maximum recharge level. Secular trends in the vertical time series show 1-3 mm/yr of subsidence across the western U.S. In areas of groundwater pumping the rates are up to several cm/yr showing subsidence as pumping exceeds annual recharge over a multi-year time period. In the mountainous areas where hydrologic loading is evident in the annual signals, secular trends show uplift of 1-3 mm/yr possibly due to regional drought and decreased overall water volumes that result in less load and vertical uplift. Overall, these results illustrate the potential of using GPS data to constrain hydrological models. In return, accurate hydrologic loading models will be needed to better measure and detect vertical tectonic motions at the mm-level.

KSC-04pd0524

NASA Image and Video Library

2004-03-05

KENNEDY SPACE CENTER, FLA. - The STS-114 crew pose for a photo in front of a solid rocket booster aft skirt in the SRB Assembly and Refurbishment Facility. In front, from left, are Cynthia Perrons, electrical technician with United Space Alliance; Commander Eileen Collins, Pilot James Kelly, and Mission Specialists Charles Camarda and Andrew Thomas. In back are Paul Gutierrez, associate program manager in SRB Element, USA; John Cleary Jr., electrical engineer with USA; Mike Leppert, project lead, Manufacturing Operations, USA; Don Noah, Materials and Processes engineer, USA; Bob Herman, deputy associate program manager, SRB Element, USA; Mission Specialist Soichi Noguchi; Dale Marlow, thermal protection system engineer with USA; Mission Specialist Stephen Robinson; Greg Henry, director, Manufacturing Operations, USA.

River Mileages and Drainage Areas for Illinois Streams. Volume 2. Illinois River Basin.

DTIC Science & Technology

1979-12-01

FLANAGAN Q. POA 33 T29N P 3E FLANAGAN 9I.1 0OAn S32 T20N R 3E FLANAGAN 1.3 POAt, S 5 T2FN W 3E FLANAGAN 12.2 POA(n 5 8 T28N d 3E FLANAGAN 14.2 NOAh S I T28...U.S..A.MY.CORPS.OF.ENGINEER..... 0..4.200..wX . .. ...... 50272 -101 REPORT DOCUMENTATION .RPRIO W IOO 4 2 S . Recipient’s Accession No. 4. Title and...SutteS. Report Date River mileages and drainage art-as for Illinois streams- December 1979 Volume 2, Illinois River Basin 6 7. Author( s ) 8. Performing

The 100th Meridian Climate Divide & Its Present and Future Impact on the Human Geography of the American Great Plains

NASA Astrophysics Data System (ADS)

Feldman, J. R.; Seager, R.; Ting, M.; Lis, N.

2016-12-01

The 100th meridian has been viewed historically as a symbolic boundary between the more arid western plains in the Midwestern United States, and the more humid eastern half of the country. The purpose of this project is to evaluate the true climatic characteristics of this divide, and to determine its implications for landscape and land use, with a focus on agriculture. An aridity index is first defined as precipitation divided by the potential evapotranspiration, P/PET, where PET is calculated with the Penman-Monteith equation using data from the North American Land Data Assimilation System Phase 2 (NLDAS-2) for the period 1979-2015. The NLDAS-2 is a compilation of observed climate data and output from three land surface models: NOAH, VIC, and MOSAIC. The three models agreed on a clear west-east gradient in aridity, with a boundary dryland boundary at approximately the 100th meridian. The aridity index was then compared to the soil moisture from each model, to determine how it impacts water storage, and the soil moisture was consistent both annually and seasonally. Using USDA data from the 2012 census, the longitudinal distribution of agricultural variables, such as farm size and percent corn of total cropland, were examined. Clear differences were observed in these variables across the aridity boundary, especially in the Northern Plains. We performed regressions between these variables and the aridity index, and found a close relationship between the aridity index and the percent of corn and wheat grown, as well as farm size. To project the potential future changes in agricultural practices due to changes in aridity, we used CMIP5 projections of the aridity index changes over the plains in the period 2040-2060. In tandem with the regression relation, we were able to predict that the percent corn of total cropland may decrease by as much as 20% at all longitudes, and it may not even be feasible to grow east of the 100th meridian. Farm size is expected to increase across the plains. Thus, we began to explore how the farm economy may be impacted by the shifting aridity gradient due to climate change in the coming century.

Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degree global warming

NASA Astrophysics Data System (ADS)

Thober, S.; Kumar, R.; Wanders, N.; Marx, A.; Pan, M.; Rakovec, O.; Samaniego, L. E.; Sheffield, J.; Wood, E. F.; Zink, M.

2017-12-01

Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 General Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over entire Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow water equivalent decreases flood events in this region. The contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share of the overall uncertainty and exceed GCM uncertainty in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but has to account for significantly higher changes under 3 K global warming.

Adapt-Mix: learning local genetic correlation structure improves summary statistics-based analyses

PubMed Central

Park, Danny S.; Brown, Brielin; Eng, Celeste; Huntsman, Scott; Hu, Donglei; Torgerson, Dara G.; Burchard, Esteban G.; Zaitlen, Noah

2015-01-01

Motivation: Approaches to identifying new risk loci, training risk prediction models, imputing untyped variants and fine-mapping causal variants from summary statistics of genome-wide association studies are playing an increasingly important role in the human genetics community. Current summary statistics-based methods rely on global ‘best guess’ reference panels to model the genetic correlation structure of the dataset being studied. This approach, especially in admixed populations, has the potential to produce misleading results, ignores variation in local structure and is not feasible when appropriate reference panels are missing or small. Here, we develop a method, Adapt-Mix, that combines information across all available reference panels to produce estimates of local genetic correlation structure for summary statistics-based methods in arbitrary populations. Results: We applied Adapt-Mix to estimate the genetic correlation structure of both admixed and non-admixed individuals using simulated and real data. We evaluated our method by measuring the performance of two summary statistics-based methods: imputation and joint-testing. When using our method as opposed to the current standard of ‘best guess’ reference panels, we observed a 28% decrease in mean-squared error for imputation and a 73.7% decrease in mean-squared error for joint-testing. Availability and implementation: Our method is publicly available in a software package called ADAPT-Mix available at https://github.com/dpark27/adapt_mix. Contact: noah.zaitlen@ucsf.edu PMID:26072481

Engaging All Americans: Innovative Strategies for Reaching the Public with Climate and Environmental Information

NASA Astrophysics Data System (ADS)

Espinoza, S.

2014-12-01

From extensive drought and heat waves to floods, tornadoes and Superstorm Sandy, extreme weather and climate events provide teachable moments to help communities prepare for and respond to related environmental, economic and health impacts. The National Environmental Education Foundation (www.neefusa.org) works with the American Meteorological Society, the media and other trusted messengers to provide weather, climate and environmental information to the public in accessible and widely used formats, whether via TV, radio or social media. NEEF will provide an overview of innovative partnerships and projects that are engaging Americans in understanding and using climate and environmental information to make the best choices in their daily lives and improve the health of their communities, including: Assessing knowledge, attitudes and behaviors: NEEF will share results from its national survey research and targeted focus groups on current attitudes and practices relating to our nation's environment. Simplifying and amplifying key messages: NEEF provides a national network of more than 350 meteorologists, radio broadcasters and journalists with the science-based information and resources they need to present climate and environmental topics to their viewers on-air, online and in community outreach. Engaging television viewers in citizen science: Eyes on Central PA, a pilot project of NEEF, Project Noah and WTAJ-TV, harnesses Project Noah's citizen science platform to collect and display photos of wildlife from WTAJ-TV viewers. NEEF and WTAJ provide regular blogs and on-air stories that highlight viewers' photos and link them to local weather conditions and climate trends. Expanding the conversation: NEEF's multimedia strategy in the Mid-Atlantic U.S. is reaching Spanish-speaking audiences with climate and environmental information through regular radio and television broadcasts. We are also exploring ways to reach other non-traditional audiences, including faith communities and sports fans, with weather, climate and preparedness information.

NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Blankenship, Clay B.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Berndt, Emily B.

2014-01-01

weather research and forecasting ===== The NASA Short-term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2-km northwestern-hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra-tropical cyclones with intense non-convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified-WRF (NU-WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real-time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU-WRF, EMS, LIS, and GSI.

Statistical evaluation of the simulated convective activity over Central Greece

NASA Astrophysics Data System (ADS)

Kartsios, Stergios; Kotsopoulos, Stylianos; Karacostas, Theodore S.; Tegoulias, Ioannis; Pytharoulis, Ioannis; Bampzelis, Dimitrios

2015-04-01

In the framework of the project DAPHNE (www.daphne-meteo.gr), the non-hydrostatic Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF-ARW, version 3.5.1) is used to produce very high spatiotemporal resolution simulations of the convective activity over Thessaly plain and hence, enhancing our knowledge on the impact of high resolution elevation and land use data in the moist convection. The expecting results act as a precursor for the potential applicability of a planned precipitation enhancement program. The three model domains, covering Europe, the Mediterranean Sea and northern Africa (d01), the wider area of Greece (d02) and Thessaly region-central Greece (d03), are used at horizontal grid-spacings of 15km, 5km and 1km respectively. ECMWF operational analyses at 6-hourly intervals (0.25ox0.25o lat.-long.) are imported as initial and boundary conditions of the coarse domain, while in the vertical, 39 sigma levels (up to 50 hPa) are used, with increased resolution in the boundary layer. Microphysical processes are represented by WSM6 scheme, sub-grid scale convection by Kain-Fritsch scheme, longwave and shortwave radiation by RRTMG scheme, surface layer by Monin-Obukhov (MM5), boundary layer by Yonsei University and soil physics by NOAH Unified model. Six representative days with different upper-air synoptic circulation types are selected, while high resolution (3'') elevation data from the Shuttle Radar Topography Mission (SRTM - version 4) are inserted in the innermost domain (d03), along with the Corine Land Cover 2000 raster data (3''x3''). The aforementioned data sets are used in different configurations, in order to evaluate the impact of each one on the simulated convective activity in the vicinity of Thessaly region, using a grid of available meteorological stations in the area. For each selected day, four (4) sensitivity simulations are performed, setting a total number of 24 runs. Finally, the best configuration provides the necessary forcing fields into a 3D Cloud model, representing a potential cloud seeding process. Acknowledgements: This research is co-financed by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" (contract number 11SYN_8_1088 - DAPHNE) in the framework of the operational programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-2013).

First experimental studies of ion flow in 3 ion species plasmas at the presheath-sheath transition

NASA Astrophysics Data System (ADS)

Severn, Greg

2016-09-01

The Bohm sheath criterion is studied with laser-induced fluorescence (LIF) in three ion species plasmas using two tunable diode lasers. KrI or HeI is added to a low pressure unmagnetized dc hot filament discharge in a mixture of argon and xenon gas confined by surface multi-dipole magnetic fields. The argon and xenon ion velocity distribution functions are measured at the sheath-presheath boundary near a negatively biased boundary plate. The potential structures of the plasma sheath and presheath are measured by an emissive probe. Results are compared with previous experiments with Ar-Xe plasmas, where the two ion species were observed to reach the sheath edge at nearly the same speed. This speed was the ion sound speed of the system, which is consistent with the generalized Bohm criterion. In such two ion species plasmas instability enhanced collisional friction (IEF) was demonstrated to exist which accounted for the observed results. When three ion species are present, it is demonstrated under most circumstances the ions do not fall out of the plasma at their individual Bohm velocities. It is also shown that under most circumstances the ions do not fall out of the plasma at the system sound speed. Results are consistent with the presence of instabilities. Author gratefully acknowledges collaborators Dr. Noah Hershkowtiz, Dr. Chi-Shung Yip, Dept. of Engineering Physics, Univ. Wisconsin-Madison, and Dr. Scott Baalrud, Dept. Physics, Univ. Iowa. Thanks to US DOE, grant DE-SC00014226.

Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degrees global warming

NASA Astrophysics Data System (ADS)

Thober, Stephan; Kumar, Rohini; Wanders, Niko; Marx, Andreas; Pan, Ming; Rakovec, Oldrich; Samaniego, Luis; Sheffield, Justin; Wood, Eric F.; Zink, Matthias

2018-01-01

Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 general circulation models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over the entirety of Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow melt equivalent decreases flood events in this region. Neglecting uncertainties originating from internal climate variability, downscaling technique, and hydrologic model parameters, the contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but have to account for significantly higher changes under 3 K global warming.

Generation of Coherent Structures After Cosmic Inflation

NASA Astrophysics Data System (ADS)

Gleiser, Marcelo

2013-04-01

The transition from inflation to power-law expansion is a rich nonlinear nonequilibrium physical process. For this reason, much is still unknown about this epoch in early universe physics, which has been dubbed the ``new big bang" by many colleagues. Here I describe results from the past few years of research, some of which in collaboration with Noah Graham and Nik Stamatopoulos, where we explored the generation on extended structures at the end of inflation known as oscillons. In particular, in hybrid inflation models we solve the coupled Einstein-Klein-Gordon equations to find that as the field responsible for inflating the universe rolls down to oscillate about its minimum, it triggers the formation of long-lived two-field oscillons, which can contribute up to 20% of the total energy density of the universe. We show that these oscillons emerge for a wide range of parameters consistent with WMAP 7-year data. These objects contain total energy of about 25x10^20 GeV, localized in a region of approximate radius 6x10-26 cm. We argue that these structures could have played a key role during the reheating of the universe, influencing the reheating temperature. We also explore the notion that these objects will appear in most symmetry-breaking phase transitions.

Solution of the Generalized Noah's Ark Problem.

PubMed

Billionnet, Alain

2013-01-01

The phylogenetic diversity (PD) of a set of species is a measure of the evolutionary distance among the species in the collection, based on a phylogenetic tree. Such a tree is composed of a root, internal nodes, and leaves that correspond to the set of taxa under study. With each edge of the tree is associated a non-negative branch length (evolutionary distance). If a particular survival probability is associated with each taxon, the PD measure becomes the expected PD measure. In the Noah's Ark Problem (NAP) introduced by Weitzman (1998), these survival probabilities can be increased at some cost. The problem is to determine how best to allocate a limited amount of resources to maximize the expected PD of the considered species. It is easy to formulate the NAP as a (difficult) nonlinear 0-1 programming problem. The aim of this article is to show that a general version of the NAP (GNAP) can be solved simply and efficiently with any set of edge weights and any set of survival probabilities by using standard mixed-integer linear programming software. The crucial point to move from a nonlinear program in binary variables to a mixed-integer linear program, is to approximate the logarithmic function by the lower envelope of a set of tangents to the curve. Solving the obtained mixed-integer linear program provides not only a near-optimal solution but also an upper bound on the value of the optimal solution. We also applied this approach to a generalization of the nature reserve problem (GNRP) that consists of selecting a set of regions to be conserved so that the expected PD of the set of species present in these regions is maximized. In this case, the survival probabilities of different taxa are not independent of each other. Computational results are presented to illustrate potentialities of the approach. Near-optimal solutions with hypothetical phylogenetic trees comprising about 4000 taxa are obtained in a few seconds or minutes of computing time for the GNAP, and in about 30 min for the GNRP. In all the cases the average guarantee varies from 0% to 1.20%.

Impact of Wildfire on Microbial Biomass in Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Murphy, M. A.; Fairbanks, D.; Chorover, J.; Gallery, R. E.; Rich, V. I.

2014-12-01

The recovery of the critical zone following disturbances such as wildfire is not fully understood. Wildfires have increased in size and intensity in western US forests in recent years and these fires influence soil microbial communities, both in composition and overall biomass. Studies have typically shown a 50% post-fire decline in overall microbial biomass (µg per g soil) that can persist for years. There is however, some variability in the severity of biomass decline, and its relationship with burn severity and landscape position have not yet been studied. Since microbial biomass has a cascade of impacts in soil systems, from helping control the rate and diversity the biogeochemical processes occurring, to promoting soil fertility, to impacting the nature and structure of soil carbon (C), fire's lasting impact on it is one mechanistic determinant of the overall post-fire recovery of impacted ecosystems. Additionally, microbial biomass measurements hold potential for testing and incorporation into land surface models (NoahMP, CLM, etc.) in order to improve estimates of long-term effects of climate change and disturbances such as fire on the C cycle. In order to refine our understanding of the impact of fire on microbial biomass and then relate that to biogeochemical processes and ecosystem recovery, we used chloroform fumigation extraction to quantify total microbial biomass C (Cmic ). One year after the June 2013 Thompson Ridge fire in the Jemez River Basin Critical Zone Observatory, we are measuring the Cmic of 22 sites across a gradient of burn severities and 4 control unburned sites, from six depth intervals at each site (0-2, 2-5, 5-10, 10-20, 20-30, and 30-40 cm). We hypothesize that the decrease in microbial biomass in burned sites relative to control sites will correlate with changes in soil biogeochemistry related to burn severity; and that the extent of the impact on biomass will be inversely related to depth in the soil column. Additionally, as the project progresses, we will relate microbial biomass to microbial functional assays as proxy for biogeochemical activity, and test variation by landscape position and aspect.

Improved regional sea-level estimates from Ice Sheets, Glaciers and land water storage using GRACE time series and other data

NASA Astrophysics Data System (ADS)

He, Z.; Velicogna, I.; Hsu, C. W.; Rignot, E. J.; Mouginot, J.; Scheuchl, B.; Fettweis, X.; van den Broeke, M. R.

2017-12-01

Changes in ice sheets, glaciers and ice caps (GIC) and land water mass cause regional sea level variations that differ significantly from a uniform re-distribution of mass over the ocean, with a decrease in sea level compared to the global mean sea level contribution (GMSL) near the sources of mass added to the ocean and an increase up to 30% larger than the GMSL in the far field. The corresponding sea level fingerprints (SLF) are difficult to separate from ocean dynamics on short time and spatial scales but as ice melt continues, the SLF signal will become increasingly dominant in the pattern of regional sea level rise. It has been anticipated that it will be another few decades before the land ice SLF could be identified in the pattern of regional sea level rise. Here, we combine 40 years of observations of ice sheet mass balance for Antarctica (1975-present) and Greenland (1978-present), along with surface mass balance reconstructions of glacier and ice caps mass balance (GIC) from 1970s to present to determine the contribution to the SLF from melting land ice (MAR and RACMO). We compare the results with observations from GRACE for the time period 2002 to present for evaluation of our approach. Land hydrology is constrained by GRACE data for the period 2002-present and by the GLDAS-NOAH land hydrology model for the longer time period. Over the long time period, we find that the contribution from land ice dominates. We quantify the contribution to the total SLF from Greenland and Antarctica in various parts of the world over the past 40 years. More important, we compare the cumulative signal from SLF with tide gauge records around the world, corrected for earth dynamics, to determine whether the land ice SLF can be detected in that record. Early results will be reported at the meeting. This work was performed at UC Irvine and at Caltech's Jet Propulsion Laboratory under a contract with NASA's Cryospheric Science Program.

Managed Relocation of Species: Noah's Ark or Pandora's Box?

NASA Astrophysics Data System (ADS)

Safford, Hugh D.; Hellmann, Jessica J.; McLachlan, Jason; Sax, Dov F.; Schwartz, Mark W.

2009-01-01

Assisted Migration: Evaluating a New Strategy for Species Conservation; Milwaukee, Wisconsin, 1-3 August 2008; The world's human population is growing rapidly. Annually we may now move more earth than natural geological processes, and our dependence on fossil fuels is causing wholesale changes in climate and many ecosystem processes. Although human impacts on the globe have long had major consequences for the Earth's other inhabitants, the current combination of massive habitat change and rapid climate change poses an especially daunting challenge for many species. Rates of anthropogenic global change, from habitat alteration to modifications of the atmosphere, are so high that many species do not possess the capacity to ``track'' these changes through natural dispersal. In addition, ``humanized'' landscapes are now so pervasive in some parts of the globe that natural dispersal corridors have all but completely disappeared.

Utopian Vision: A Grand Solution for a Scholarly Dilemma.

PubMed

Watts, Roderick J

2017-06-01

Reconciling the Zen-like paradox on the back of every red penny-"out of many, one"-is not for the faint of heart. It is a diversity motto, and a lofty desire that the United States claims to covet. But can its citizens, undocumented or otherwise, even agree on what it is? Is not the desire to maintain a strong sense of community in conflict with a Noah's Ark conception of diversity? Using my personal experience in an intentional community determined to foster racial integration, I explore the complicated possibility of having it both ways. To do so, however, we must construct a notion of community, diversity, and The Good Life that will make us believe and work for this synthesis. Our reactions to the word "utopia" offer a glimpse of the challenges ahead. © Society for Community Research and Action 2017.

Core issues in the economics of biodiversity conservation.

PubMed

Tisdell, Clement A

2011-02-01

Economic evaluations are essential for assessing the desirability of biodiversity conservation. This article highlights significant advances in theories and methods of economic evaluation and their relevance and limitations as a guide to biodiversity conservation; considers the implications of the phylogenetic similarity principle for the survival of species; discusses consequences of the Noah's Ark problem for selecting features of biodiversity to be saved; analyzes the extent to which the precautionary principle can be rationally used to support the conservation of biodiversity; explores the impact of market extensions, market and other institutional failures, and globalization on biodiversity loss; examines the relationship between the rate of interest and biodiversity depletion; and investigates the implications of intergenerational equity for biodiversity conservation. The consequences of changes in biodiversity for sustainable development are given particular attention. © 2011 New York Academy of Sciences.

Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

NASA Astrophysics Data System (ADS)

Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

2016-02-01

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

Noah's Ark conservation will not preserve threatened ecological communities under climate change.

PubMed

Harris, Rebecca Mary Bernadette; Carter, Oberon; Gilfedder, Louise; Porfirio, Luciana Laura; Lee, Greg; Bindoff, Nathaniel Lee

2015-01-01

Effective conservation of threatened ecological communities requires knowledge of where climatically suitable habitat is likely to persist into the future. We use the critically endangered Lowland Grassland community of Tasmania, Australia as a case study to identify options for management in cases where future climatic conditions become unsuitable for the current threatened community. We model current and future climatic suitability for the Lowland Themeda and the Lowland Poa Grassland communities, which make up the listed ecological community. We also model climatic suitability for the structurally dominant grass species of these communities, and for closely related grassland and woodland communities. We use a dynamically downscaled regional climate model derived from six CMIP3 global climate models, under the A2 SRES emissions scenario. All model projections showed a large reduction in climatically suitable area by mid-century. Outcomes are slightly better if closely related grassy communities are considered, but the extent of suitable area is still substantially reduced. Only small areas within the current distribution are projected to remain climatically suitable by the end of the century, and very little of that area is currently in good condition. As the climate becomes less suitable, a gradual change in the species composition, structure and habitat quality of the grassland communities is likely. Conservation management will need to focus on maintaining diversity, structure and function, rather than attempting to preserve current species composition. Options for achieving this include managing related grassland types to maintain grassland species at the landscape-scale, and maximising the resilience of grasslands by reducing further fragmentation, weed invasion and stress from other land uses, while accepting that change is inevitable. Attempting to maintain the status quo by conserving the current structure and composition of Lowland Grassland communities is unlikely to be a viable management option in the long term.

A multiphysics and multiscale software environment for modeling astrophysical systems

NASA Astrophysics Data System (ADS)

Portegies Zwart, Simon; McMillan, Steve; Harfst, Stefan; Groen, Derek; Fujii, Michiko; Nualláin, Breanndán Ó.; Glebbeek, Evert; Heggie, Douglas; Lombardi, James; Hut, Piet; Angelou, Vangelis; Banerjee, Sambaran; Belkus, Houria; Fragos, Tassos; Fregeau, John; Gaburov, Evghenii; Izzard, Rob; Jurić, Mario; Justham, Stephen; Sottoriva, Andrea; Teuben, Peter; van Bever, Joris; Yaron, Ofer; Zemp, Marcel

2009-05-01

We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a "Noah's Ark" milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multiscale and multiphysics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe three examples calculated using MUSE: the merger of two galaxies, the merger of two evolving stars, and a hybrid N-body simulation. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.li.

Comparison of Decadal Water Storage Trends from Global Hydrological Models and GRACE Satellite Data

NASA Astrophysics Data System (ADS)

Scanlon, B. R.; Zhang, Z. Z.; Save, H.; Sun, A. Y.; Mueller Schmied, H.; Van Beek, L. P.; Wiese, D. N.; Wada, Y.; Long, D.; Reedy, R. C.; Doll, P. M.; Longuevergne, L.

2017-12-01

Global hydrology is increasingly being evaluated using models; however, the reliability of these global models is not well known. In this study we compared decadal trends (2002-2014) in land water storage from 7 global models (WGHM, PCR-GLOBWB, and GLDAS: NOAH, MOSAIC, VIC, CLM, and CLSM) to storage trends from new GRACE satellite mascon solutions (CSR-M and JPL-M). The analysis was conducted over 186 river basins, representing about 60% of the global land area. Modeled total water storage trends agree with those from GRACE-derived trends that are within ±0.5 km3/yr but greatly underestimate large declining and rising trends outside this range. Large declining trends are found mostly in intensively irrigated basins and in some basins in northern latitudes. Rising trends are found in basins with little or no irrigation and are generally related to increasing trends in precipitation. The largest decline is found in the Ganges (-12 km3/yr) and the largest rise in the Amazon (43 km3/yr). Differences between models and GRACE are greatest in large basins (>0.5x106 km2) mostly in humid regions. There is very little agreement in storage trends between models and GRACE and among the models with values of r2 mostly <0.1. Various factors can contribute to discrepancies in water storage trends between models and GRACE, including uncertainties in precipitation, model calibration, storage capacity, and water use in models and uncertainties in GRACE data related to processing, glacier leakage, and glacial isostatic adjustment. The GRACE data indicate that land has a large capacity to store water over decadal timescales that is underrepresented by the models. The storage capacity in the modeled soil and groundwater compartments may be insufficient to accommodate the range in water storage variations shown by GRACE data. The inability of the models to capture the large storage trends indicates that model projections of climate and human-induced changes in water storage may be mostly underestimated. Future GRACE and model studies should try to reduce the various sources of uncertainty in water storage trends and should consider expanding the modeled storage capacity of the soil profiles and their interaction with groundwater.

Project NOAH: Regulating modern sea-level rise. Phase II: Jerusalem Underground

NASA Astrophysics Data System (ADS)

Newman, Walter S.; Fairbridge, Rhodes W.

This proposal builds a high-speed inter-urban express between Jerusalem and Tel Aviv, generates 1500 megawatts of hydroelectric energy, curtails littoral erosion, builds a port along the Israeli Mediterranean coast and demands peaceful cooperation on both sides of the Jordan River. Phase II represents a pilot project demonstrating the feasibility of continuing to regulate world sea-level by a new series of water regulation schemes. Phase I previously described all those projects already completed or underway which have inadvertently and/or unintentionally served the purpose of sea-level regulation. These forms of Phase I sea-level regulation include large and small reservoirs, irrigation projects, water infiltration schemes, farm ponds, and swimming and reflecting pools. All these water storage projects have already exercised a very appreciable brake on 20th century sea-level rise. Phase II outlines a high-visibility proposal which will serve to illustrate the viability of “Project NOAH”.

Comparative education and the ?new? sociologies

NASA Astrophysics Data System (ADS)

Trusz, Andrew R.; Parks-Trusz, Sandra L.

1981-12-01

The authors examine the impact of the `new' sociologies on comparative education by reviewing five comparative readers published during the past twenty years. While the `new' sociologies have had considerable impact within sociology and the sociology of education, minimal impact is found within comparative education. The authors further show that while critical new sociologies such as Marxism, neo-Marxism, and Critical theory have had some penetration into comparative education, use of the interpretative sociologies such as symbolic interactionism, ethnomethodology, and semiotics has generally been absent. The authors conclude by suggesting that a synthesis of the critical and interpretative modes would prove fruitful for further work in comparative education. The five texts are: Halsey, Floud and Anderson (eds.), Education, Economy and Society (1961); Eckstein and Noah (eds.), Scientific Investigations in Comparative Education (1969); Beck, Perspectives on World Education (1970); Karabel and Halsey (eds.), Power and Ideology in Education (1977); and Altbach and Kelly (eds.), Education and Colonialism (1978).

The Moses, mega-Moses, and Armstrong illusions: integrating language comprehension and semantic memory.

PubMed

Shafto, M; MacKay, D G

2000-09-01

This study develops a new theory of the Moses illusion, observed in responses to general knowledge questions such as, "How many animals of each kind did Moses take on the Ark?" People often respond "two" rather than "zero" despite knowing that Noah, not Moses, launched the Ark. Our theory predicted two additional types of conceptual error demonstrated here: the Armstrong and mega-Moses illusions. The Armstrong illusion involved questions resembling, "What was the famous line uttered by Louis Armstrong when he first set foot on the moon?" People usually comprehend such questions as valid, despite knowing that Louis Armstrong was a jazz musician who never visited the moon. This Armstrong illusion was not due to misperceiving the critical words (Louis Armstrong), and occurred as frequently as the Moses illusion (with critical words embedded in identical sentential contexts), but less frequently than the mega-Moses illusion caused when Moses and Armstrong factors were combined.

Automated peak picking and peak integration in macromolecular NMR spectra using AUTOPSY.

PubMed

Koradi, R; Billeter, M; Engeli, M; Güntert, P; Wüthrich, K

1998-12-01

A new approach for automated peak picking of multidimensional protein NMR spectra with strong overlap is introduced, which makes use of the program AUTOPSY (automated peak picking for NMR spectroscopy). The main elements of this program are a novel function for local noise level calculation, the use of symmetry considerations, and the use of lineshapes extracted from well-separated peaks for resolving groups of strongly overlapping peaks. The algorithm generates peak lists with precise chemical shift and integral intensities, and a reliability measure for the recognition of each peak. The results of automated peak picking of NOESY spectra with AUTOPSY were tested in combination with the combined automated NOESY cross peak assignment and structure calculation routine NOAH implemented in the program DYANA. The quality of the resulting structures was found to be comparable with those from corresponding data obtained with manual peak picking. Copyright 1998 Academic Press.

Resource-aware taxon selection for maximizing phylogenetic diversity.

PubMed

Pardi, Fabio; Goldman, Nick

2007-06-01

Phylogenetic diversity (PD) is a useful metric for selecting taxa in a range of biological applications, for example, bioconservation and genomics, where the selection is usually constrained by the limited availability of resources. We formalize taxon selection as a conceptually simple optimization problem, aiming to maximize PD subject to resource constraints. This allows us to take into account the different amounts of resources required by the different taxa. Although this is a computationally difficult problem, we present a dynamic programming algorithm that solves it in pseudo-polynomial time. Our algorithm can also solve many instances of the Noah's Ark Problem, a more realistic formulation of taxon selection for biodiversity conservation that allows for taxon-specific extinction risks. These instances extend the set of problems for which solutions are available beyond previously known greedy-tractable cases. Finally, we discuss the relevance of our results to real-life scenarios.

Companionship in the neighborhood context: Older adults’ living arrangements and perceptions of social cohesion

PubMed Central

Bromell, Lea; Cagney, Kathleen A.

2014-01-01

This study investigated the impact of neighborhood social cohesion on the perceived companionship of nearly 1,500 community-dwelling older adults from the Neighborhood, Organization, Aging and Health project (NOAH), a Chicago-based study of older adult well-being in the neighborhood context. We hypothesized that the relationship between neighborhood-level social cohesion and individual residents’ reports of companionship would be more pronounced among those who lived alone than those who resided with others. Controlling for age, gender, education, race, marital status, length of neighborhood residence, and self-rated health, neighborhood social cohesion predicted companionship among those who lived alone; for a one-unit increase in neighborhood social cohesion, the odds of reporting companionship increased by half. In contrast, social cohesion did not predict the companionship of those who resided with others. The results suggest that older adults who live alone particularly profit from the benefits of socially cohesive neighborhood environments. PMID:24860203

Communication interface and graphic module for audiometry equipment.

PubMed

Gutiérrez Martinez, Josefina; Barraza López, Fernando; Guadarrama Lara, Alberto; Núñez Gaona, Marco Antonio; Delgado Esquerra, Ruth; Gutiérrez Farfán, Ileana

2009-01-01

The National Rehabilitation Institute (INR) in Mexico City purchased 12 Madsen Orbiter 922 audiometers in 2006. While this audiometer is excellent for diagnosing the degree and type of hearing loss, it has presented problems in transfering, saving and printing the results of special tests and logoaudiometry from audiometer to workstation with the NOAH-3 system. The data are lost when the audiometer is turned off or a new patient is captured. There is no database storing and, shortly after the results have been printed on the thermal paper, the audiograms are erased. This problem was addressed by designing and implementing the InterAudio (AAMS) communication and graphical interface. The limitations and scope of the Automatic Audiometric Measurement System were analyzed, then a search of technical information was performed that included the resources for designing, developing and implementing the transfer interface, the user's graphical module requirements, and the tools for printing and saving the study.

Investigating the relation between the geometric properties of river basins and the filtering parameters for regional land hydrology applications using GRACE models

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sideris, Michael G.

2016-04-01

This study investigates the possibilities of local hydrology signal extraction using GRACE data and conventional filtering techniques. The impact of the basin shape has also been studied in order to derive empirical rules for tuning the GRACE filter parameters. GRACE CSR Release 05 monthly solutions were used from April 2002 to August 2015 (161 monthly solutions in total). SLR data were also used to replace the GRACE C2,0 coefficient, and a de-correlation filter with optimal parameters for CSR Release 05 data was applied to attenuate the correlation errors of monthly mass differences. For basins located at higher latitudes, the effect of Glacial Isostatic Adjustment (GIA) was taken into account using the ICE-6G model. The study focuses on three geometric properties, i.e., the area, the convexity and the width in the longitudinal direction, of 100 basins with global distribution. Two experiments have been performed. The first one deals with the determination of the Gaussian smoothing radius that minimizes the gaussianity of GRACE equivalent water height (EWH) over the selected basins. The EWH kurtosis was selected as a metric of gaussianity. The second experiment focuses on the derivation of the Gaussian smoothing radius that minimizes the RMS difference between GRACE data and a hydrology model. The GLDAS 1.0 Noah hydrology model was chosen, which shows good agreement with GRACE data according to previous studies. Early results show that there is an apparent relation between the geometric attributes of the basins examined and the Gaussian radius derived from the two experiments. The kurtosis analysis experiment tends to underestimate the optimal Gaussian radius, which is close to 200-300 km in many cases. Empirical rules for the selection of the Gaussian radius have been also developed for sub-regional scale basins.

A Quantum Annealing Computer Team Addresses Climate Change Predictability

NASA Technical Reports Server (NTRS)

Halem, M. (Principal Investigator); LeMoigne, J.; Dorband, J.; Lomonaco, S.; Yesha, Ya.; Simpson, D.; Clune, T.; Pelissier, C.; Nearing, G.; Gentine, P.;

Identification of Critical Vulnerable Areas During a Typhoon Haiyan Event in the Metro Manila Area Using Storm Surge Hazard Maps

NASA Astrophysics Data System (ADS)

Briones, J. B. L. T.; Puno, J. V.; Lapidez, J. P. B.; Muldong, T. M. M.; Ramos, M. M.; Caro, C. V.; Ladiero, C.; Bahala, M. A.; Suarez, J. K. B.; Santiago, J. T.

2014-12-01

Sudden rises in sea water over and above astronomical tides due to an approaching storm are known as storm surges. The development of an early warning system for storm surges is imperative, due to the high threat level of these events; Typhoon Haiyan in 08 November 2013 generated storm surges that caused casualties of over 6,000. Under the Department of Science and Technology, the Nationwide Operational Assessment of Hazards (DOST - Project NOAH) was tasked to generate storm surge hazard maps for all the coastal areas in the Philippines. The objective of this paper is to create guidelines on how to utilize the storm surge hazard map as a tool for planning and disaster mitigation. This study uses the case of the hypothetical situation in which a tropical storm with an intensity similar to Typhoon Haiyan hits Metro Manila. This site was chosen for various reasons, among them the economic, political, and cultural importance of Metro Manila as the location of the capital of the Philippines and the coastal bay length of the area. The concentration of residential areas and other establishments were also taken into account. Using the Japan Meteorology Association (JMA) Storm Surge Model, FLO-2D flood modelling software and the application of other GIS technology, the impact of Haiyan-strength typhoon passing through Manila was analysed. We were able to identify the population affected, number of affected critical facilities under each storm surge hazard level, and possible evacuation sites. The results of the study can be used as the basis of policies involving disaster response and mitigation by city authorities. The methods used by the study can be used as a replicable framework for the analysis of other sites in the Philippines.

Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas.

PubMed

Xu, Boyan; Su, Lu; Wang, Zhenxiong; Fan, Yang; Gong, Gaolang; Zhu, Wenzhen; Gao, Peiyi; Gao, Jia-Hong

2018-04-17

Anomalous diffusion model has been introduced and shown to be beneficial in clinical applications. However, only the directionally averaged values of anomalous diffusion parameters were investigated, and the anisotropy of anomalous diffusion remains unexplored. The aim of this study was to demonstrate the feasibility of using anisotropy of anomalous diffusion for differentiating low- and high-grade cerebral gliomas. Diffusion MRI images were acquired from brain tumor patients and analyzed using the fractional motion (FM) model. Twenty-two patients with histopathologically confirmed gliomas were selected. An anisotropy metric for the FM-related parameters, including the Noah exponent (α) and the Hurst exponent (H), was introduced and their values were statistically compared between the low- and high-grade gliomas. Additionally, multivariate logistic regression analysis was performed to assess the combination of the anisotropy metric and the directionally averaged value for each parameter. The diagnostic performances for grading gliomas were evaluated using a receiver operating characteristic (ROC) analysis. The Hurst exponent H was more anisotropic in high-grade than in low-grade gliomas (P = 0.015), while no significant difference was observed for the anisotropy of α. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of α (1) and the combination of H (0.813) compared with the directionally averaged α (0.979) and H (0.594), indicating an improved performance for tumor differentiation. The anisotropy of anomalous diffusion can provide distinctive information and benefit the differentiation of low- and high-grade gliomas. The utility of anisotropic anomalous diffusion may have an improved effect for investigating pathological changes in tissues. Copyright © 2018 Elsevier Inc. All rights reserved.

Disaster management as part of curriculum for undergraduate and postgraduate courses: The Symbiosis model

PubMed Central

Deshpande, Vijay

2011-01-01

From times immemorial disasters in some form or the other have been regularly visiting humankind and humans have been trying to manage these upheavals. Noah's arch is the first such endeavor. The United Nations declared 1990-1999 as International Decade for Disaster Reduction. The Indian Government passed the Disaster Management Act 2005. As a consequence of the Act, the National Disaster Management Authority was setup. All states were given the guide lines for disaster risk reduction. The objective of this article is to get a clearer picture of what various states, educational authorities and international bodies have done and what Symbiosis International University (SIU) has done so far. Inputs from various States of the Indian Union and neighboring countries were studied. The moot question that figured all the time was “Is there a conscious effort to include Disaster Management in the curricula of various courses at the college and university level” and what are the achievements. It was seen that the Central Board for Secondary Education with support from the Ministry of Home Affairs, Ministry of Human Resource Development and United Nations Development Project have incorporated DM, as part of its frontline curriculum. Most of the Universities in the disaster prone states have enunciated policies for including DM in the curriculum, but palpable results are still awaited. In the SIU, DM has been incorporated in the curriculum and is mandatory for all undergraduate and postgraduate courses. PMID:22412285

Disaster management as part of curriculum for undergraduate and postgraduate courses: The Symbiosis model.

PubMed

Deshpande, Vijay

2011-09-01

From times immemorial disasters in some form or the other have been regularly visiting humankind and humans have been trying to manage these upheavals. Noah's arch is the first such endeavor. The United Nations declared 1990-1999 as International Decade for Disaster Reduction. The Indian Government passed the Disaster Management Act 2005. As a consequence of the Act, the National Disaster Management Authority was setup. All states were given the guide lines for disaster risk reduction. The objective of this article is to get a clearer picture of what various states, educational authorities and international bodies have done and what Symbiosis International University (SIU) has done so far. Inputs from various States of the Indian Union and neighboring countries were studied. The moot question that figured all the time was "Is there a conscious effort to include Disaster Management in the curricula of various courses at the college and university level" and what are the achievements. It was seen that the Central Board for Secondary Education with support from the Ministry of Home Affairs, Ministry of Human Resource Development and United Nations Development Project have incorporated DM, as part of its frontline curriculum. Most of the Universities in the disaster prone states have enunciated policies for including DM in the curriculum, but palpable results are still awaited. In the SIU, DM has been incorporated in the curriculum and is mandatory for all undergraduate and postgraduate courses.

Multi-model ensemble simulations of low flows in Europe under a 1.5, 2, and 3 degree global warming

NASA Astrophysics Data System (ADS)

Marx, A.; Kumar, R.; Thober, S.; Zink, M.; Wanders, N.; Wood, E. F.; Pan, M.; Sheffield, J.; Samaniego, L. E.

2017-12-01

There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e., 1.5, 2 and 3 K). The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three RCPs (rcp2p6, rcp6p0, rcp8p5), five CMIP5 GCMs (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High resolution model results are available at the unprecedented spatial resolution of 5 km across the pan-European domain at daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90% of the time. It is determined separately for each GCM/HM combinations and the warming scenarios. The results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from -12% under 1.5 K to -35% under 3 K global warming largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22% (1.5 K) to +45% (3 K) because of the reduced snow melt contribution. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Nevertheless, it is not possible to distinguish climate induced differences in low flows between 1.5 and 2 K warming because of the large variability inherent in the multi-model ensemble. The contribution by the GCMs to the uncertainty in the Alpine and Northern region as well as the Mediterranean, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration.

Memory and the Moses illusion: failures to detect contradictions with stored knowledge yield negative memorial consequences.

PubMed

Bottoms, Hayden C; Eslick, Andrea N; Marsh, Elizabeth J

2010-08-01

Although contradictions with stored knowledge are common in daily life, people often fail to notice them. For example, in the Moses illusion, participants fail to notice errors in questions such as "How many animals of each kind did Moses take on the Ark?" despite later showing knowledge that the Biblical reference is to Noah, not Moses. We examined whether error prevalence affected participants' ability to detect distortions in questions, and whether this in turn had memorial consequences. Many of the errors were overlooked, but participants were better able to catch them when they were more common. More generally, the failure to detect errors had negative memorial consequences, increasing the likelihood that the errors were used to answer later general knowledge questions. Methodological implications of this finding are discussed, as it suggests that typical analyses likely underestimate the size of the Moses illusion. Overall, answering distorted questions can yield errors in the knowledge base; most importantly, prior knowledge does not protect against these negative memorial consequences.

Companionship in the neighborhood context: older adults' living arrangements and perceptions of social cohesion.

PubMed

Bromell, Lea; Cagney, Kathleen A

2014-03-01

This study investigated the impact of neighborhood social cohesion on the perceived companionship of nearly 1,500 community-dwelling older adults from the Neighborhood, Organization, Aging and Health project (NOAH), a Chicago-based study of older adult well-being in the neighborhood context. We hypothesized that the relationship between neighborhood-level social cohesion and individual residents' reports of companionship would be more pronounced among those who lived alone than those who resided with others. Controlling for age, gender, education, race, marital status, length of neighborhood residence, and self-rated health, neighborhood social cohesion predicted companionship among those who lived alone; for a one-unit increase in neighborhood social cohesion, the odds of reporting companionship increased by half. In contrast, social cohesion did not predict the companionship of those who resided with others. The results suggest that older adults who live alone particularly profit from the benefits of socially cohesive neighborhood environments. © The Author(s) 2013.

External quality assurance project report for the National Atmospheric Deposition Program’s National Trends Network and Mercury Deposition Network, 2015–16

USGS Publications Warehouse

Wetherbee, Gregory A.; Martin, RoseAnn

2018-06-29

The U.S. Geological Survey Precipitation Chemistry Quality Assurance project operated five distinct programs to provide external quality assurance monitoring for the National Atmospheric Deposition Program’s (NADP) National Trends Network and Mercury Deposition Network during 2015–16. The National Trends Network programs include (1) a field audit program to evaluate sample contamination and stability, (2) an interlaboratory comparison program to evaluate analytical laboratory performance, and (3) a colocated sampler program to evaluate bias and variability attributed to automated precipitation samplers. The Mercury Deposition Network programs include the (4) system blank program and (5) an interlaboratory comparison program. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends for chemical constituents in wet deposition.The field audit program results indicate increased sample contamination for calcium, magnesium, and potassium relative to 2010 levels, and slight fluctuation in sodium contamination. Nitrate contamination levels dropped slightly during 2014–16, and chloride contamination leveled off between 2007 and 2016. Sulfate contamination is similar to the 2000 level. Hydrogen ion contamination has steadily decreased since 2012. Losses of ammonium and nitrate resulting from potential sample instability were negligible.The NADP Central Analytical Laboratory produced interlaboratory comparison results with low bias and variability compared to other domestic and international laboratories that support atmospheric deposition monitoring. Significant absolute bias above the magnitudes of the detection limits was observed for nitrate and sulfate concentrations, but no analyte determinations exceeded the detection limits for blanks.Colocated sampler program results from dissimilar colocated collectors indicate that the retrofit of the National Trends Network with N-CON Systems Company, Inc. precipitation collectors could cause substantial shifts in NADP annual deposition (concentration multiplied by depth) values. Median weekly relative percent differences for analyte concentrations ranged from -4 to +76 percent for cations, from 5 to 6 percent for ammonium, from +14 to +25 percent for anions, and from -21 to +8 percent for hydrogen ion contamination. By comparison, weekly absolute concentration differences for paired identical N-CON Systems Company, Inc., collectors ranged from 4–22 percent for cations; 2–9 percent for anions; 4–5 percent for ammonium; and 13–14 percent for hydrogen ion contamination. The N-CON Systems Company, Inc. collector caught more precipitation than the Aerochem Metrics Model 301 collector (ACM) at the WA99/99WA sites, but it typically caught slightly less precipitation than the ACM at ND11/11ND, sites which receive more wind and snow than WA99/99WA.Paired, identical OTT Pluvio-2 and ETI Noah IV precipitation gages were operated at the same sites. Median absolute percent differences for daily measured precipitation depths ranged from 0 to 7 percent. Annual absolute differences ranged from 0.08 percent (ETI Noah IV precipitation gages) to 11 percent (OTT Pluvio-2 precipitation gages).The Mercury Deposition Network programs include the system blank program and an interlaboratory comparison program. System blank results indicate that maximum total mercury contamination concentrations in samples were less than the third percentile of all Mercury Deposition Network sample concentrations (1.098 nanograms per liter; ng/L). The Mercury Analytical Laboratory produced chemical concentration results with low bias and variability compared with other domestic and international laboratories that support atmospheric-deposition monitoring. The laboratory’s performance results indicate a +1-ng/L shift in bias between 2015 (-0.4 ng/L) and 2016 (+0.5 ng/L).

Investigating the variation of terrestrial water storage under changing climate and land cover

NASA Astrophysics Data System (ADS)

Fang, Y.; Niu, G. Y.; Zhang, X.; Troch, P. A. A.

2015-12-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture, snow and ice, lakes and rivers and water contained in biomass. The water storage, especially the subsurface storage, is an essential property of the catchment, which controls climate, hydrological and biogeochemical processes at different scales. During the past decades, climate and land cover change has been proved to exert significant influences on hydrological processes which in turn alters the TWS variation. In order to better understand the interaction and feedback mechanism between TWS and earth system, it is necessary to quantify the effects of climate and land cover change on TWS variation. Direct estimation of total TWS has been made possible by the Gravity Recovery And Climate Experiment (GRACE) satellites that measures the earth gravity field. At present, few efforts were made to explicitly investigate the TWS variation under changing climate and land cover. GRACE data has its own limitations. One is its temporal coverage is short, it's only available since 2002, which is not sufficient to reflect the trend due to climate and land cover change. The other reason is that it cannot distinguish different components contributing to TWS. The limitation of TWS observation data can be overcame by numerical models developed to reproduce or to predict different earth system processes. After calibration and validation, with limited observations, these models can be trusted to extend our knowledge to where observations are not available both in time and space. In this study, based on Noah-MP LSM and satellite and ground data, we aim to: (1) Investigate the variation of total TWS as well as its components over Upper Colorado River Basin from 1990 to 2014. (2) Identify the major factors that control the TWS variation. (3) Quantify how the changing climate and land cover affect TWS variation in the same period.

Developing an early warning system for storm surge inundation in the Philippines

NASA Astrophysics Data System (ADS)

Tablazon, Judd; Mahar Francisco Lagmay, Alfredo; Francia Mungcal, Ma. Theresa; Gonzalo, Lia Anne; Dasallas, Lea; Briones, Jo Brianne Louise; Santiago, Joy; Suarez, John Kenneth; Lapidez, John Phillip; Caro, Carl Vincent; Ladiero, Christine; Malano, Vicente

2014-05-01

A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 08 November 2013 where more than 6,000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency (JMA) Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10-minute intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

Developing an early warning system for storm surge inundation in the Philippines

NASA Astrophysics Data System (ADS)

Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

2014-10-01

A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013 where more than 6000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10 min intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

Can mountain glacier melting explains the GRACE-observed mass loss in the southeast Tibetan Plateau: From a climate perspective?

NASA Astrophysics Data System (ADS)

Song, Chunqiao; Ke, Linghong; Huang, Bo; Richards, Keith S.

2015-01-01

The southeast Tibetan Plateau (SETP) includes the majority of monsoonal temperate glaciers in High Mountain Asia (HMA), which is an important source of water for the upper reaches of several large Asian river systems. Climatic change and variability has substantial impacts on cryosphere and hydrological processes in the SETP. The Gravity Recovery and Climate Experiment (GRACE) gravimetry observations between 2003 and 2009 suggest that there was an average mass loss rate of - 5.99 ± 2.78 Gigatonnes (Gt)/yr in this region. Meanwhile, the hydrological data by model calculations from the GLDAS/Noah and CPC are used to estimate terrestrial water storage (TWS) changes with a slight negative trend of about - 0.3 Gt/yr. The recent studies (Kääb et al., 2012; Gardner et al., 2013) reported the thinning rates of mountain glaciers in HMA based on the satellite laser altimetry, and an approximate estimation of the glacier mass budget in the SETP was 4.69 ± 2.03 Gt/yr during 2003-2009. This estimate accounted for a large proportion ( 78.3%) of the difference between the GRACE TWS and model-calculated TWS changes. To better understand the cause of sharp mass loss existing in the SETP, the correlations between key climatic variables (precipitation and temperature) and the GRACE TWS changes are examined at different timescales between 2003 and 2011. The results show that precipitation is the leading factors of abrupt, seasonal and multi-year undulating signals of GRACE TWS anomaly time series, but with weak correlations with the inter-annual trend and annual mass budget of GRACE TWS. In contrast, the annual mean temperature is tightly associated with the annual net mass budget (r = 0.81, p < 0.01), which indirectly suggests that the GRACE-observed mass loss in the SETP may be highly related to glacial processes.

High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe

NASA Astrophysics Data System (ADS)

Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.

2017-12-01

For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.

Drought and heatwaves in Europe: historical reconstruction and future projections

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Rakovec, Olda; Wood, Eric; Sheffield, Justin; Pan, Ming; Wanders, Niko; Prudhomme, Christel

2017-04-01

Heat waves and droughts are creeping hydro-meteorological events that may bring societies and natural systems to their limits by inducing large famines, increasing health risks to the population, creating drinking and irrigation water shortfalls, inducing natural fires and degradation of soil and water quality, and in many cases causing large socio-economic losses. Europe, in particular, has endured large scale drought-heat-wave events during the recent past (e.g., 2003 European drought), which have induced enormous socio-economic losses as well as casualties. Recent studies showed that the prediction of droughts and heatwaves is subject to large-scale forcing and parametric uncertainties that lead to considerable uncertainties in the projections of extreme characteristics such as drought magnitude/duration and area under drought, among others. Future projections are also heavily influenced by the RCP scenario uncertainty as well as the coarser spatial resolution of the models. The EDgE project funded by the Copernicus programme (C3S) provides an unique opportunity to investigate the evolution of droughts and heatwaves from 1950 until 2099 over the Pan-EU domain at a scale of 5x5 km2. In this project, high-resolution multi-model hydrologic simulations with the mHM (www.ufz.de/mhm), Noah-MP, VIC and PCR-GLOBWB have been completed for the historical period 1955-2015. Climate projections have been carried out with five CMIP-5 GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M from 2006 to 2099 under RCP2.6 and RCP8.5. Using these multi-model unprecedented simulations, daily soil moisture index and temperature anomalies since 1955 until 2099 will be estimated. Using the procedure proposed by Samaniego et al. (2013), the probabilities of exceeding the benchmark events in the reference period 1980-2010 will be estimated for each RCP scenario. References http://climate.copernicus.eu/edge-end-end-demonstrator-improved-decision-making-water-sector-europe Samaniego, L., R. Kumar, and M. Zink, 2013: Implications of parameter uncertainty on soil moisture drought analysis in Germany. J. Hydrometeor., 14, 47-68, doi:10.1175/JHM-D-12-075.1. Samaniego, L., et al. 2016: Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins. Climatic Change. 1-15.

The truth about mouse, human, worms and yeast

PubMed Central

2004-01-01

Genome comparisons are behind the powerful new annotation methods being developed to find all human genes, as well as genes from other genomes. Genomes are now frequently being studied in pairs to provide cross-comparison datasets. This 'Noah's Ark' approach often reveals unsuspected genes and may support the deletion of false-positive predictions. Joining mouse and human as the cross-comparison dataset for the first two mammals are: two Drosophila species, D. melanogaster and D. pseudoobscura; two sea squirts, Ciona intestinalis and Ciona savignyi; four yeast (Saccharomyces) species; two nematodes, Caenorhabditis elegans and Caenorhabditis briggsae; and two pufferfish (Takefugu rubripes and Tetraodon nigroviridis). Even genomes like yeast and C. elegans, which have been known for more than five years, are now being significantly improved. Methods developed for yeast or nematodes will now be applied to mouse and human, and soon to additional mammals such as rat and dog, to identify all the mammalian protein-coding genes. Current large disparities between human Unigene predictions (127,835 genes) and gene-scanning methods (45,000 genes) still need to be resolved. This will be the challenge during the next few years. PMID:15601543

The truth about mouse, human, worms and yeast.

PubMed

Nelson, David R; Nebert, Daniel W

2004-01-01

Genome comparisons are behind the powerful new annotation methods being developed to find all human genes, as well as genes from other genomes. Genomes are now frequently being studied in pairs to provide cross-comparison datasets. This 'Noah's Ark' approach often reveals unsuspected genes and may support the deletion of false-positive predictions. Joining mouse and human as the cross-comparison dataset for the first two mammals are: two Drosophila species, D. melanogaster and D. pseudoobscura; two sea squirts, Ciona intestinalis and Ciona savignyi; four yeast (Saccharomyces) species; two nematodes, Caenorhabditis elegans and Caenorhabditis briggsae; and two pufferfish (Takefugu rubripes and Tetraodon nigroviridis). Even genomes like yeast and C. elegans, which have been known for more than five years, are now being significantly improved. Methods developed for yeast or nematodes will now be applied to mouse and human, and soon to additional mammals such as rat and dog, to identify all the mammalian protein-coding genes. Current large disparities between human Unigene predictions (127,835 genes) and gene-scanning methods (45,000 genes) still need to be resolved. This will be the challenge during the next few years.

Genomic localization of the human gene encoding Dr1, a negative modulator of transcription of class II and class III genes.

PubMed

Purrello, M; Di Pietro, C; Rapisarda, A; Viola, A; Corsaro, C; Motta, S; Grzeschik, K H; Sichel, G

1996-01-01

Dr1 is a nuclear protein of 19 kDa that exists in the nucleoplasm as a homotetramer. By binding to TBP (the DNA-binding subunit of TFIID, and also a subunit of SL1 and TFIIIB), the protein blocks class II and class III preinitiation complex assembly, thus repressing the activity of the corresponding promoters. Since transcription of class I genes is unaffected by Dr1. it has been proposed that the protein may coordinate the expression of class I, class II and class III genes. By somatic cell genetics and fluorescence in situ hybridization, we have localized the gene (DR1), present in the genome of higher eukaryotes as a single copy, to human chromosome region 1p21-->p13. The nucleotide sequence conservation of the coding segment of the gene, as determined by Noah's ark blot analysis, and its ubiquitous transcription suggest that Dr1 has an important biological role, which could be related to the negative control of cell proliferation.

Psychotherapist mindfulness and the psychotherapy process.

PubMed

Bruce, Noah; Bruce, Noah G; Shapiro, Shauna L; Constantino, Michael J; Manber, Rachel

2010-03-01

[Correction Notice: An erratum for this article was reported in Vol 47(2) of Psychotherapy: Theory, Research & Practice (see record 2010-13424-005). the order of authorship and the affiliations of the authors was incorrectly printed. The correct order and affiliations are as follows: Noah Bruce, Shauna L. Shapiro, Michael J. Constantino, and Rachel Manber; Kaiser Permanente, Santa Clara University, University of Massachusetts, Stanford University] A psychotherapist's ability to relate to his or her patients is essential for decreasing patient suffering and promoting patient growth. However, the psychotherapy field has identified few effective means for training psychotherapists in this ability. In this conceptual article, we propose that mindfulness practice may be a means for training psychotherapists to better relate to their patients. We posit that mindfulness is a means of self-attunement that increases one's ability to attune to others (in this case, patients) and that this interpersonal attunement ultimately helps patients achieve greater self-attunement that, in turn, fosters decreased symptom severity, greater well-being, and better interpersonal relationships. PsycINFO Database Record (c) 2010 APA, all rights reserved

A Rapid Protoyping Approach for the Evaluation of Potential GPM-Era Precipitation Products for Water Resources Management Applications

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Houser, P. R.; Turk, F. J.; Peterson, C. A.; Hossain, F.; Moorhead, R. J.; Toll, D. L.; Mostovoy, G.

2009-04-01

In order to facilitate the operational transition of satellite data, research products and advances in numerical modeling, the NASA Applied Sciences Program (ASP) had adopted a systems engineering approach to help identify and advanced and basic research capabilities that may be further developed for operational applications. This novel approach was envisioned to accelerate the harvesting of NASA's investment in research for societal benefits. International programs such as the Global Earth Observing System of Systems (GEOSS) could benefit from such systematic and integrated approaches to identify and extend the results of earth and environmental sciences for the benefits of global society. This new approach by the ASP was based on three phases of implementation, namely: (a) "Solutions Networks" for systematically examining data products, capabilities, and results from NASA Earth science research in order to find identify and prioritize candidate research activities that have the potential for societal benefits; (b) "Rapid Prototyping Capability (RPC)" experiments to further develop and tailor basic research and further evaluate and quantify their potential impacts for applications and decision support; and (c) "Integrated System Solutions (ISS)" to fully execute the transition the research to operational implementation and benchmark the performance resulting from integrating NASA Earth observations and science results. The RPC science experiments can be rapidly prototyped in order to evaluate the suitability of data, algorithms and models. They are designed to characterize uncertainties involved in the data, models, and decision making process while maintaining scientific rigor through the entire process. This approach helps identify scientific and logistical risks earlier in the process so that they can be appropriately addressed in a timely manner to minimize risk. GPM is promoted as "a science mission with broad societal applications," that will address societal benefits related to human health (soil moisture, climate and disease outbreak), homeland security (removal of chemical/biological/nuclear agents), flooding potential and warning, water availability, water quality, and agriculture and food security. In 2006, the NASA ASP sponsored two RPC experiments to evaluate potential GPM-era high resolution satellite precipitation products for water management applications. One of the current uncertainties involved in the GPM missions is the nature of the exact configuration of the constellations of satellites and hence the potential for the dynamic error characteristics over time of the precipitation estimates. For the RPC evaluations, we needed a satellite precipitation product that would be analogous to the GPM-era products. Our solution was to develop a suite of high resolution precipitation products, based on the NRL-Blend algorithm. We created a set of 10 different satellite precipitation estimates (hereafter referred to as the "GPM-proxy data"), using the currently available IR and microwave sensors. However, in each product we systematically left out sets of observations and/or sensors, such as AM orbits. The geographical focus of our study was the operational domain of the Arkansas Basin River Forecast Center (ABRFC) of the U.S. National Weather Service. We have evaluated the GPM-proxy data against the operational product (radar and gauge based) used by ABRFC. Further, we also performed a set of soil water content (SWC) sensitivity experiments using the Noah and Mosaic Land Surface Models (LSM) to quantify the impacts on water management applications involving land surface hydrology. Both the LSMs were forced with the same set of GPM-proxy data. Though the overall spatial patterns for both the models were similar, there were subtle differences in the respective model sensitivities to the different precipitation forcings. These experimental results illustrate the need for comprehensive pre-evaluations of applications, in order quantify and minimize the risks involved in applications with the introduction of new precipitation products, before making extensive investments in operational transitions. Besides the SWC sensitivity experiments, we have also evaluated precipitation merging and downscaling techniques using various other precipitation products, including IR-based estimates, NRL-Blend and CMORPH. During the presentation, we will outline systems engineering approach used by ASP, summarize the results of the GPM RPC experiments, and discuss the lessons learned in prototyping applications for GPM-era high resolution precipitation products.

Homogeneity testing of the global ESA CCI multi-satellite soil moisture climate data record

NASA Astrophysics Data System (ADS)

Preimesberger, Wolfgang; Su, Chun-Hsu; Gruber, Alexander; Dorigo, Wouter

2017-04-01

ESA's Climate Change Initiative (CCI) creates a global, long-term data record by merging multiple available earth observation products with the goal to provide a product for climate studies, trend analysis, and risk assessments. The blending of soil moisture (SM) time series derived from different active and passive remote sensing instruments with varying sensor characteristics, such as microwave frequency, signal polarization or radiometric accuracy, could potentially lead to inhomogeneities in the merged long-term data series, undercutting the usefulness of the product. To detect the spatio-temporal extent of contiguous periods without inhomogeneities as well as subsequently minimizing their negative impact on the data records, different relative homogeneity tests (namely Fligner-Killeen test of homogeneity of variances and Wilcoxon rank-sums test) are implemented and tested on the combined active-passive ESA CCI SM data set. Inhomogeneities are detected by comparing the data against reference data from in-situ data from ISMN, and model-based estimates from GLDAS-Noah and MERRA-Land. Inhomogeneity testing is performed over the ESA CCI SM data time frame of 38 years (from 1978 to 2015), on a global quarter-degree grid and with regard to six alterations in the combination of observation systems used in the data blending process. This study describes and explains observed variations in the spatial and temporal patterns of inhomogeneities in the combined products. Besides we proposes methodologies for measuring and reducing the impact of inhomogeneities on trends derived from the ESA CCI SM data set, and suggest the use of inhomogeneity-corrected data for future trend studies. This study is supported by the European Union's FP7 EartH2Observe "Global Earth Observation for Integrated Water Resource Assessment" project (grant agreement number 331 603608).

Mount Ararat, Turkey, Perspective with Landsat Image Overlay

NASA Technical Reports Server (NTRS)

2004-01-01

This perspective view shows Mount Ararat in easternmost Turkey, which has been the site of several searches for the remains of Noah's Ark. The main peak, known as Great Ararat, is the tallest peak in Turkey, rising to 5165 meters (16,945 feet). This southerly, near horizontal view additionally shows the distinctly conically shaped peak known as 'Little Ararat' on the left. Both peaks are volcanoes that are geologically young, but activity during historic times is uncertain.

This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 1.25-times vertical exaggeration to enhance topographic expression. Natural colors of the scene are enhanced by image processing, inclusion of some infrared reflectance (as green) to highlight the vegetation pattern, and inclusion of shading of the elevation model to further highlight the topographic features.

Volcanoes pose hazards for people, the most obvious being the threat of eruption. But other hazards are associated with volcanoes too. In 1840 an earthquake shook the Mount Ararat region, causing an unstable part of mountain's north slope to tumble into and destroy a village. Visualizations of satellite imagery when combined with elevation models can be used to reveal such hazards leading to disaster prevention through improved land use planning.

But the hazards of volcanoes are balanced in part by the benefits they provide. Over geologic time volcanic materials break down to form fertile soils. Cultivation of these soils has fostered and sustained civilizations, as has occurred in the Mount Ararat region. Likewise, tall volcanic peaks often catch precipitation, providing a water supply to those civilizations. Mount Ararat hosts an icefield and set of glaciers, as seen here in this late summer scene, that are part of this beneficial natural process

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space Administration (NASA), the National Geospatial-Intelligence Agency (NGA) of the U.S. Department of Defense (DoD), and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Earth Science Enterprise, Washington, DC.

View Size: 124 kilometers (77 miles) wide, 148 kilometers (92 miles) distance Location: 39.7 degrees North latitude, 44.3 degrees East longitude Orientation: Looking South, 2 degrees down from horizontal, 1.25X vertical exaggeration Image Data: Landsat Bands 1, 2+4, 3 as blue, green, red respectively Date Acquired: February 2000 (SRTM), August 31, 1989 (Landsat)

Space Shuttle Program

NASA Image and Video Library

2012-09-12

Ronnie Rigney (r), chief of the Propulsion Test Office in the Project Directorate at Stennis Space Center, stands with agency colleagues to receive the prestigious American Institute of Aeronautics and Astronautics George M. Low Space Transportation Award on Sept. 12. Rigney accepted the award on behalf of the NASA and contractor team at Stennis for their support of the Space Shuttle Program that ended last summer. From 1975 to 2009, Stennis Space Center tested every main engine used to power 135 space shuttle missions. Stennis continued to provide flight support services through the end of the Space Shuttle Program in July 2011. The center also supported transition and retirement of shuttle hardware and assets through September 2012. The 2012 award was presented to the space shuttle team 'for excellence in the conception, development, test, operation and retirement of the world's first and only reusable space transportation system.' Joining Rigney for the award ceremony at the 2012 AIAA Conference in Pasadena, Calif., were: (l to r) Allison Zuniga, NASA Headquarters; Michael Griffin, former NASA administrator; Don Noah, Johnson Space Center in Houston; Steve Cash, Marshall Space Flight Center in Huntsville, Ala.; and Pete Nickolenko, Kennedy Space Center in Florida.

GSFC_20180130_M12842_Supermoon

NASA Image and Video Library

2018-01-30

Get ready for the Super Blue Blood Moon! Our closest celestial neighbor is always a wondrous sight, but on the morning of Jan. 31, 2018, three special lunar events are all happening at the same time, providing an excellent excuse to go out and enjoy the nighttime sky. 1 - The full Moon is near the closest point of its orbit so it appears a little larger than usual, what many call a Supermoon. 2 - It’s the second full Moon of the month, what many call a Blue Moon, though the Moon is not literally blue. 3 - There’s a total lunar eclipse, what many call a Blood Moon, visible before sunrise for the western half of the U.S. and other countries near the Pacific. During a total lunar eclipse, the Moon crosses through the shadow of the Earth and LITERALLY appears red as it reflects all of Earth’s sunrises and sunsets. Join NASA scientists Michelle Thaller and Noah Petro live from the Goddard Space Flight Center as we discuss where, when, and how to view this lunar extravaganza and the latest Moon science brought to us by NASA’s Lunar Reconnaissance Orbiter.

Hearing Device Manufacturers Call for Interoperability and Standardization of Internet and Audiology.

PubMed

Laplante-Lévesque, Ariane; Abrams, Harvey; Bülow, Maja; Lunner, Thomas; Nelson, John; Riis, Søren Kamaric; Vanpoucke, Filiep

2016-10-01

This article describes the perspectives of hearing device manufacturers regarding the exciting developments that the Internet makes possible. Specifically, it proposes to join forces toward interoperability and standardization of Internet and audiology. A summary of why such a collaborative effort is required is provided from historical and scientific perspectives. A roadmap toward interoperability and standardization is proposed. Information and communication technologies improve the flow of health care data and pave the way to better health care. However, hearing-related products, features, and services are notoriously heterogeneous and incompatible with other health care systems (no interoperability). Standardization is the process of developing and implementing technical standards (e.g., Noah hearing database). All parties involved in interoperability and standardization realize mutual gains by making mutually consistent decisions. De jure (officially endorsed) standards can be developed in collaboration with large national health care systems as well as spokespeople for hearing care professionals and hearing device users. The roadmap covers mutual collaboration; data privacy, security, and ownership; compliance with current regulations; scalability and modularity; and the scope of interoperability and standards. We propose to join forces to pave the way to the interoperable Internet and audiology products, features, and services that the world needs.

Comparison of the Structurally Controlled Landslides Numerical Model Results to the M 7.2 2013 Bohol Earthquake Co-seismic Landslides

NASA Astrophysics Data System (ADS)

Macario Galang, Jan Albert; Narod Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo

2015-04-01

The M 7.2 October 15, 2013 Bohol earthquake is the most destructive earthquake to hit the Philippines since 2012. The epicenter was located in Sagbayan municipality, central Bohol and was generated by a previously unmapped reverse fault called the "Inabanga Fault". Its name, taken after the barangay (village) where the fault is best exposed and was first seen. The earthquake resulted in 209 fatalities and over 57 billion USD worth of damages. The earthquake generated co-seismic landslides most of which were related to fault structures. Unlike rainfall induced landslides, the trigger for co-seismic landslides happen without warning. Preparedness against this type of landslide therefore, relies heavily on the identification of fracture-related unstable slopes. To mitigate the impacts of co-seismic landslide hazards, morpho-structural orientations or discontinuity sets were mapped in the field with the aid of a 2012 IFSAR Digital Terrain Model (DTM) with 5-meter pixel resolution and < 0.5 meter vertical accuracy. Coltop 3D software was then used to identify similar structures including measurement of their dip and dip directions. The chosen discontinuity sets were then keyed into Matterocking software to identify potential rock slide zones due to planar or wedged discontinuities. After identifying the structurally-controlled unstable slopes, the rock mass propagation extent of the possible rock slides was simulated using Conefall. The results were compared to a post-earthquake landslide inventory of 456 landslides. Out the total number of landslides identified from post-earthquake high-resolution imagery, 366 or 80% intersect the structural-controlled hazard areas of Bohol. The results show the potential of this method to identify co-seismic landslide hazard areas for disaster mitigation. Along with computer methods to simulate shallow landslides, and debris flow paths, located structurally-controlled unstable zones can be used to mark unsafe areas for settlement. The method can be further improved with the use of Lidar DTMs, which has better accuracy than the IFSAR DTM. A nationwide effort under DOST-Project NOAH (DREAM-LIDAR) is underway, to map the Philippine archipelago using Lidar.

Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products

NASA Astrophysics Data System (ADS)

Shamsudduha, Mohammad; Taylor, Richard G.; Jones, Darren; Longuevergne, Laurent; Owor, Michael; Tindimugaya, Callist

2017-09-01

GRACE (Gravity Recovery and Climate Experiment) satellite data monitor large-scale changes in total terrestrial water storage (ΔTWS), providing an invaluable tool where in situ observations are limited. Substantial uncertainty remains, however, in the amplitude of GRACE gravity signals and the disaggregation of TWS into individual terrestrial water stores (e.g. groundwater storage). Here, we test the phase and amplitude of three GRACE ΔTWS signals from five commonly used gridded products (i.e. NASA's GRCTellus: CSR, JPL, GFZ; JPL-Mascons; GRGS GRACE) using in situ data and modelled soil moisture from the Global Land Data Assimilation System (GLDAS) in two sub-basins (LVB: Lake Victoria Basin; LKB: Lake Kyoga Basin) of the Upper Nile Basin. The analysis extends from January 2003 to December 2012, but focuses on a large and accurately observed reduction in ΔTWS of 83 km3 from 2003 to 2006 in the Lake Victoria Basin. We reveal substantial variability in current GRACE products to quantify the reduction of ΔTWS in Lake Victoria that ranges from 80 km3 (JPL-Mascons) to 69 and 31 km3 for GRGS and GRCTellus respectively. Representation of the phase in TWS in the Upper Nile Basin by GRACE products varies but is generally robust with GRGS, JPL-Mascons, and GRCTellus (ensemble mean of CSR, JPL, and GFZ time-series data), explaining 90, 84, and 75 % of the variance respectively in "in situ" or "bottom-up" ΔTWS in the LVB. Resolution of changes in groundwater storage (ΔGWS) from GRACE ΔTWS is greatly constrained by both uncertainty in changes in soil-moisture storage (ΔSMS) modelled by GLDAS LSMs (CLM, NOAH, VIC) and the low annual amplitudes in ΔGWS (e.g. 1.8-4.9 cm) observed in deeply weathered crystalline rocks underlying the Upper Nile Basin. Our study highlights the substantial uncertainty in the amplitude of ΔTWS that can result from different data-processing strategies in commonly used, gridded GRACE products; this uncertainty is disregarded in analyses of ΔTWS and individual stores applying a single GRACE product.

Noise in DORIS station position time series provided by IGN-JPL, INASAN and CNES-CLS Analysis Centres for the ITRF2014 realization

NASA Astrophysics Data System (ADS)

Khelifa, Sofiane

2016-12-01

The purpose of this paper is to compare the noise characteristics in DORIS station positions between the three solutions derived by IGN-JPL (named as IGN), INASAN (named as INA) and CNES-CLS (named as LCA) Analysis Centres for ITRF2014 contribution, and to evaluate the improvements of these reprocessed solutions in terms of noise level with the previous ITRF2008 solutions. To the weekly STCD (STation Coordinate Difference) residual position time series of 23 stations referred to ITRF2008 and expressed in the local frame (North, East and Up), we calculated the Allan variance to identify their noise type, and applied the wavelet transform to assess their annual and semi-annual signals, and their noise level. The results reveal that the three solutions are dominated by white noise in all three components. The noise level is the lowest in the LCA solution; the average noise level in respectively, North, East and Vertical components is around 5.9 mm, 9.3 mm and 6.6 mm for LCA, 9 mm, 11.6 mm and 9 mm for IGN, and 8.7 mm, 11.6 mm and 9.1 mm for INA. The results also show that the tropical (±23.5°) stations are more distorted than mid-latitude and high latitude stations. In terms of noise level, the reprocessed LCA solution (lca14wd40) and its previous solution (lca11wd02) converge to similar results, while the reprocessed IGN (ign14wd15) and INA (ina14wd08) solutions show improvements with respect to their previous solutions (ign11wd01) and (ina12wd01) respectively, especially in the East component. Furthermore, the possible origin of the estimated annual signal was also investigated by comparing it with hydrology and atmospheric loading displacements. The annual Vertical component for the three solutions is more correlated with the GLDAS/Noah hydrology model with an average correlation of about 0.35, and shows a strong correlation of about 0.76 with ECMWF-IB and ECMWF-MOG2D atmospheric models for the station Krasnoyarsk (KRBB) in Siberia.

Direct N2O Fluxes from Agroecosystems in Cold Climates: Importance of Soil Freeze-Thaw

NASA Astrophysics Data System (ADS)

Congreves, K. A.; Wagner-Riddle, C.; Abalos, D.; Ambadan, J. T.; Brown, S. E.; Tenuta, M.; Gao, X.; Amiro, B. D.; Berg, A. A.

2016-12-01

To develop effective climate change mitigation strategies and reduce N2O emissions, the global contribution of freeze-thaw cycles from croplands must be characterized; we present the first study to do so. Long-term N2O flux datasets from micrometeorological approaches were compiled from two Canadian sites (Elora ON & Glenlea MB). Measurements encompassed a total of 21-yr on 16-ha of land producing annual field crops, yielding an unprecedented record of N2O fluxes (42118 half-hourly values) at sites subjected to freeze-thaw cycles from Nov-Apr. At Elora (the warmer site) N2O flux events were associated with thaw cycles throughout Nov-Apr and the main thaw event took place between mid/end of April when air temperatures rose above 0°C and snow melted. The continental site (Glenlea) did not have significant N2O flux events during the prolonged freeze period, but had considerably higher emissions over the thaw period when soil temperature and liquid water content increased more slowly than Elora. Based on cumulative N2O emissions from both sites (Nov-Apr), emissions were closely related to freezing degree days (FDD). An exponential-to-plateau model significantly fit (p<0.0001, r= 0.72) the relationship between N2O emissions and FDD, characterizing larger N2O emissions as FDD increased (y=1.95 (1-exp-0.00852x), y=cumulative N2O-N kg ha-1 and x=FDD). To estimate the global contribution of N2O emissions from seasonally frozen croplands in the northern hemisphere, we applied the algorithm to a global map of FDD derived from three reanalysis products (ERA-Interim, MERRA-Land, GLDAS-NOAH) combined with MODIS land fraction data for croplands. Average global freeze-thaw induced N2O emissions for croplands was estimated at 1.07 Tg N, though it may range from 0.79 - 1.35 Tg N due to model error and variation. This global contribution of N2O from seasonally frozen cropland soils may be responsible for previously observed discrepancies between top-down and bottom-up approaches.

Detecting seasonal and long-term vertical displacement in the North China Plain using GRACE and GPS

NASA Astrophysics Data System (ADS)

Wang, Linsong; Chen, Chao; Du, Jinsong; Wang, Tongqing

2017-06-01

In total, 29 continuous Global Positioning System (GPS) time series data together with data from Gravity Recovery and Climate Experiment (GRACE) are analysed to determine the seasonal displacements of surface loadings in the North China Plain (NCP). Results show significant seasonal variations and a strong correlation between GPS and GRACE results in the vertical displacement component; the average correlation and weighted root-mean-squares (WRMS) reduction between GPS and GRACE are 75.6 and 28.9 % respectively, when atmospheric and non-tidal ocean effects were removed, but the annual peak-to-peak amplitude of GPS (1.2-6.3 mm) is greater than the data (1.0-2.2 mm) derived from GRACE. We also calculate the trend rate as well as the seasonal signal caused by the mass load change from GRACE data; the rate of GRACE-derived terrestrial water storage (TWS) loss (after multiplying by the scaling factor) in the NCP was 3.39 cm yr-1 (equivalent to 12.42 km3 yr-1) from 2003 to 2009. For a 10-year time span (2003 to 2012), the rate loss of TWS was 2.57 cm yr-1 (equivalent to 9.41 km3 yr-1), which is consistent with the groundwater storage (GWS) depletion rate (the rate losses of GWS were 2.49 and 2.72 cm yr-1 during 2003-2009 and 2003-2012 respectively) estimated from GRACE-derived results after removing simulated soil moisture (SM) data from the Global Land Data Assimilation System (GLDAS)/Noah model. We also found that GRACE-derived GWS changes are in disagreement with the groundwater level changes from observations of shallow aquifers from 2003 to 2009, especially between 2010 and 2013. Although the shallow groundwater can be recharged from the annual climate-driven rainfall, the important facts indicate that GWS depletion is more serious in deep aquifers. The GRACE-derived result shows an overall uplift in the whole region at the 0.37-0.95 mm yr-1 level from 2004 to 2009, but the rate of change direction is inconsistent in different GPS stations at the -0.40-0.51 mm yr-1 level from 2010 to 2013. Then we removed the vertical rates, which are induced by TWS from GPS-derived data, to obtain the corrected vertical velocities caused by tectonic movement and human activities. The results show that there are uplift areas and subsidence areas in NCP. Almost the whole central and eastern region of NCP suffers serious ground subsidence caused by the anthropogenic-induced groundwater exploitation in the deep confined aquifers. In addition, the slight ground uplifts in the western region of NCP are mainly controlled by tectonic movement (e.g. Moho uplifting or mantle upwelling).

Computing Incompressible Flows With Free Surfaces

NASA Technical Reports Server (NTRS)

Kothe, D.

1994-01-01

RIPPLE computer program models transient, two-dimensional flows of incompressible fluids with surface tension on free surfaces of general shape. Surface tension modeled as volume force derived from continuum-surface-force model, giving RIPPLE both robustness and accuracy in modeling surface-tension effects at free surface. Also models wall adhesion effects. Written in FORTRAN 77.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Surface models of the male urogenital organs built from the Visible Korean using popular software

PubMed Central

Shin, Dong Sun; Park, Jin Seo; Shin, Byeong-Seok

2011-01-01

Unlike volume models, surface models, which are empty three-dimensional images, have a small file size, so they can be displayed, rotated, and modified in real time. Thus, surface models of male urogenital organs can be effectively applied to an interactive computer simulation and contribute to the clinical practice of urologists. To create high-quality surface models, the urogenital organs and other neighboring structures were outlined in 464 sectioned images of the Visible Korean male using Adobe Photoshop; the outlines were interpolated on Discreet Combustion; then an almost automatic volume reconstruction followed by surface reconstruction was performed on 3D-DOCTOR. The surface models were refined and assembled in their proper positions on Maya, and a surface model was coated with actual surface texture acquired from the volume model of the structure on specially programmed software. In total, 95 surface models were prepared, particularly complete models of the urinary and genital tracts. These surface models will be distributed to encourage other investigators to develop various kinds of medical training simulations. Increasingly automated surface reconstruction technology using commercial software will enable other researchers to produce their own surface models more effectively. PMID:21829759

High-resolution multimodel projections of soil moisture drought in Europe under 1.5, 2 and 3 degree global warming

NASA Astrophysics Data System (ADS)

Samaniego, L. E.; Kumar, R.; Zink, M.; Pan, M.; Wanders, N.; Marx, A.; Sheffield, J.; Wood, E. F.; Thober, S.

2017-12-01

Droughts are creeping hydro-meteorological events that may bring societies and natural systems to their limits by inducing significant environmental changes and large socio-economic losses. Little is know about the effects of varios degrees of warming (i.e., 1.5 , 2 and 3 K) and their respective uncertainties on extreme characteristics such as drought duration and area under drought in general, and in Europe in particular. In this study we investigate the evolution of droughts characteristics under three levels of warming using an unprecedented high-resolution multi-model hydrologic ensemble over the Pan-EU domain at a scale of 5x5 km2 from 1950 until 2100. This multi-model ensemble comprises four hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB, VIC) which are forced by five CMIP-5 Global Climate Models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) under three RCP scenarios 2.6, 6.0, and 8.5. This results in a 60-member ensemble. The contribution GCM/HM uncertainties were analyzed based on a sequential sampling algorithm proposed by Samaniego et al. 2016. This study is carried out within the EDgE project funded by the Copernicus Climate Change Service (edge.climate.copernicus.eu) and the HOKLIM project funded by the German Ministry of Education (BMBF)(www.ufz.de/hoklim). The changes under three levels of warming indicate significant increase (more than 10%) of the number of droughts and area under drought with respect to 30-year climatological means obtained with E-OBS observations. Furthermore, we found that: 1) the number of drought events exhibit significant regional changes. Largest changes are observed in the Mediterrinian where frequency of droughts increases from 25% under 1.5 K to 33% under 2 K, and to more than 50% under 3 K warming. Minor changes are seen in Central-Europe and the British Isles. 2) The GCMs/HMs uncertainties have marked regional differences too, with GCM uncertainty appear to be larger everywhere. The uncertainty of HMs are, however, similar to those of the GCMs in the Iberian peninsula due to different representation of evapotranspiration and soil moisture dynamics. And, 3) despite the large uncertainty in the full ensemble, significant positive trends have been observed in all drought characteristics that intensify with increased global warming.

The effect of working memory load on semantic illusions: what the phonological loop and central executive have to contribute.

PubMed

Büttner, Anke Caroline

2012-01-01

When asked how many animals of each kind Moses took on the Ark, most people respond with "two" despite the substituted name (Moses for Noah) in the question. Possible explanations for semantic illusions appear to be related to processing limitations such as those of working memory. Indeed, individual working memory capacity has an impact upon how sentences containing substitutions are processed. This experiment examined further the role of working memory in the occurrence of semantic illusions using a dual-task working memory load approach. Participants verified statements while engaging in either articulatory suppression or random number generation. Secondary task type had a significant effect on semantic illusion rate, but only when comparing the control condition to the two dual-task conditions. Furthermore, secondary task performance in the random number generation condition declined, suggesting a tradeoff between tasks. Response time analyses also showed a different pattern of processing across the conditions. The findings suggest that the phonological loop plays a role in representing semantic illusion sentences coherently and in monitoring for details, while the role of the central executive is to assist gist-processing of sentences. This usually efficient strategy leads to error in the case of semantic illusions.

Modeling equine race surface vertical mechanical behaviors in a musculoskeletal modeling environment.

PubMed

Symons, Jennifer E; Fyhrie, David P; Hawkins, David A; Upadhyaya, Shrinivasa K; Stover, Susan M

2015-02-26

Race surfaces have been associated with the incidence of racehorse musculoskeletal injury, the leading cause of racehorse attrition. Optimal race surface mechanical behaviors that minimize injury risk are unknown. Computational models are an economical method to determine optimal mechanical behaviors. Previously developed equine musculoskeletal models utilized ground reaction floor models designed to simulate a stiff, smooth floor appropriate for a human gait laboratory. Our objective was to develop a computational race surface model (two force-displacement functions, one linear and one nonlinear) that reproduced experimental race surface mechanical behaviors for incorporation in equine musculoskeletal models. Soil impact tests were simulated in a musculoskeletal modeling environment and compared to experimental force and displacement data collected during initial and repeat impacts at two racetracks with differing race surfaces - (i) dirt and (ii) synthetic. Best-fit model coefficients (7 total) were compared between surface types and initial and repeat impacts using a mixed model ANCOVA. Model simulation results closely matched empirical force, displacement and velocity data (Mean R(2)=0.930-0.997). Many model coefficients were statistically different between surface types and impacts. Principal component analysis of model coefficients showed systematic differences based on surface type and impact. In the future, the race surface model may be used in conjunction with previously developed the equine musculoskeletal models to understand the effects of race surface mechanical behaviors on limb dynamics, and determine race surface mechanical behaviors that reduce the incidence of racehorse musculoskeletal injury through modulation of limb dynamics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding Surface Adhesion in Nature: A Peeling Model.

PubMed

Gu, Zhen; Li, Siheng; Zhang, Feilong; Wang, Shutao

2016-07-01

Nature often exhibits various interesting and unique adhesive surfaces. The attempt to understand the natural adhesion phenomena can continuously guide the design of artificial adhesive surfaces by proposing simplified models of surface adhesion. Among those models, a peeling model can often effectively reflect the adhesive property between two surfaces during their attachment and detachment processes. In the context, this review summarizes the recent advances about the peeling model in understanding unique adhesive properties on natural and artificial surfaces. It mainly includes four parts: a brief introduction to natural surface adhesion, the theoretical basis and progress of the peeling model, application of the peeling model, and finally, conclusions. It is believed that this review is helpful to various fields, such as surface engineering, biomedicine, microelectronics, and so on.

Numerical study of electromagnetic scattering from one-dimensional nonlinear fractal sea surface

NASA Astrophysics Data System (ADS)

Xie, Tao; He, Chao; William, Perrie; Kuang, Hai-Lan; Zou, Guang-Hui; Chen, Wei

2010-02-01

In recent years, linear fractal sea surface models have been developed for the sea surface in order to establish an electromagnetic backscattering model. Unfortunately, the sea surface is always nonlinear, particularly at high sea states. We present a nonlinear fractal sea surface model and derive an electromagnetic backscattering model. Using this model, we numerically calculate the normalized radar cross section (NRCS) of a nonlinear sea surface. Comparing the averaged NRCS between linear and nonlinear fractal models, we show that the NRCS of a linear fractal sea surface underestimates the NRCS of the real sea surface, especially for sea states with high fractal dimensions, and for dominant ocean surface gravity waves that are either very short or extremely long.

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

NASA Astrophysics Data System (ADS)

Marx, Andreas; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Wanders, Niko; Zink, Matthias; Wood, Eric F.; Pan, Ming; Sheffield, Justin; Samaniego, Luis

2018-02-01

There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000 km2. The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5 km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90 % of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from -12 % under 1.5 K, compared to the baseline period 1971-2000, to -35 % under global warming of 3 K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5 K) to +45 % (3 K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2 K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of period-averaged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multi-model ensemble as well as its single members in the adaptation process.

Understanding Surface Adhesion in Nature: A Peeling Model

PubMed Central

Gu, Zhen; Li, Siheng; Zhang, Feilong

2016-01-01

Nature often exhibits various interesting and unique adhesive surfaces. The attempt to understand the natural adhesion phenomena can continuously guide the design of artificial adhesive surfaces by proposing simplified models of surface adhesion. Among those models, a peeling model can often effectively reflect the adhesive property between two surfaces during their attachment and detachment processes. In the context, this review summarizes the recent advances about the peeling model in understanding unique adhesive properties on natural and artificial surfaces. It mainly includes four parts: a brief introduction to natural surface adhesion, the theoretical basis and progress of the peeling model, application of the peeling model, and finally, conclusions. It is believed that this review is helpful to various fields, such as surface engineering, biomedicine, microelectronics, and so on. PMID:27812476

High frequency acoustic propagation under variable sea surfaces

NASA Astrophysics Data System (ADS)

Senne, Joseph

This dissertation examines the effects of rough sea surfaces and sub-surface bubbles on high frequency acoustic transmissions. Owing to the strong attenuation of electromagnetic waves in seawater, acoustic waves are used in the underwater realm much in the same way that electromagnetic waves are used in the atmosphere. The transmission and reception of acoustic waves in the underwater environment is important for a variety of fields including navigation, ocean observation, and real-time communications. Rough sea surfaces and sub-surface bubbles alter the acoustic signals that are received not only in the near-surface water column, but also at depth. This dissertation demonstrates that surface roughness and sub-surface bubbles notably affect acoustic transmissions with frequency ranges typical of underwater communications systems (10-50 kHz). The influence of rough surfaces on acoustic transmissions is determined by modeling forward propagation subject to sea surface dynamics that vary with time scales of less than a second to tens of seconds. A time-evolving rough sea surface model is combined with a rough surface formulation of a parabolic equation model for predicting time-varying acoustic fields. Linear surface waves are generated from surface wave spectra, and evolved in time using a Runge-Kutta integration technique. This evolving, range-dependent surface information is combined with other environmental parameters and fed into the acoustic model, giving an approximation of the time-varying acoustic field. The wide-angle parabolic equation model manages the rough sea surfaces by molding them into the boundary conditions for calculations of the near-surface acoustic field. The influence of sub-surface bubbles on acoustic transmissions is determined by modeling the population of bubbles near the surface and using those populations to approximate the effective changes in sound speed and attenuation. Both range-dependent and range-independent bubble models are considered, with the range-dependent model varying over the same time scales as the sea surface model and the range-independent model invariant over time. The bubble-induced sound speed and attenuation fluctuations are read in by the parabolic equation model, which allows for the effects of surface roughness and sub-surface bubbles to be computed separately or together. These merged acoustic models are validated using concurrently-collected acoustic and environmental information, including surface wave spectra. Data to model comparisons demonstrate that the models are able to approximate the ensemble-averaged acoustic intensity at ranges of at least a kilometer for acoustic signals of 10-20 kHz. The rough surface model is shown to capture variations due to surface fluctuations occurring over time scales of less than a second to tens of seconds. The separate bubble models demonstrate the abilities to account for the intermittency of bubble plumes and to determine overall effect of bubbly layers, respectively. The models are shown to capture variations in the acoustic field occurring over time scales of less than a second to tens of seconds. Comparisons against data demonstrate the ability of the model to track acoustic transmissions under evolving sea surfaces. The effects of the evolving bubble field are demonstrated through the use of idealized test cases. For frequency ranges important to communications, surface roughness is shown to have the more dominant effect, with bubbles having an ancillary effect.

Replication of surface features from a master model to an amorphous metallic article

DOEpatents

Johnson, William L.; Bakke, Eric; Peker, Atakan

1999-01-01

The surface features of an article are replicated by preparing a master model having a preselected surface feature thereon which is to be replicated, and replicating the preselected surface feature of the master model. The replication is accomplished by providing a piece of a bulk-solidifying amorphous metallic alloy, contacting the piece of the bulk-solidifying amorphous metallic alloy to the surface of the master model at an elevated replication temperature to transfer a negative copy of the preselected surface feature of the master model to the piece, and separating the piece having the negative copy of the preselected surface feature from the master model.

A COUPLED LAND-SURFACE AND DRY DEPOSITION MODEL AND COMPARISON TO FIELD MEASUREMENTS OF SURFACE HEAT, MOISTURE, AND OZONE FLUXES

EPA Science Inventory

We have developed a coupled land-surface and dry deposition model for realistic treatment of surface fluxes of heat, moisture, and chemical dry deposition within a comprehensive air quality modeling system. A new land-surface model (LSM) with explicit treatment of soil moisture...

EDgE multi-model hydro-meteorological seasonal hindcast experiments over Europe

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Rakovec, Oldrich; Wood, Eric; Sheffield, Justin; Pan, Ming; Wanders, Niko; Prudhomme, Christel

2017-04-01

Extreme hydrometeorological events (e.g., floods, droughts and heat waves) caused serious damage to society and infrastructures over Europe during the past decades. Developing a seamless and skillful operational seasonal forecasting system of these extreme events is therefore a key tool for short-term decision making at local and regional scales. The EDgE project funded by the Copernicus programme (C3S) provides an unique opportunity to investigate the skill of a newly created large multi-model hydro-meteorological ensemble for predicting extreme events over the Pan-EU domain at a higher resolution 5×5 km2. Two state-of-the-art seasonal prediction systems were chosen for this project. Two models from the North American MultiModel ensemble (NMME) with 22 realizations, and two models provided by the ECMWF with 30 realizations. All models provide daily forcings (P, Ta, Tmin, Tmax) of the the Pan-EU at 1°. Downscaling has been carried out with the MTCLIM algorithm (Bohn et al. 2013) and external drift Kriging using elevation as drift to induce orographic effects. In this project, four high-resolution seamless hydrologic simulations with the mHM (www.ufz.de/mhm), Noah-MP, VIC and PCR-GLOBWB have been completed for the common hindcast period of 1993-2012 resulting in an ensemble size of 208 realizations. Key indicators are focussing on six terrestrial Essential Climate Variables (tECVs): river runoff, soil moisture, groundwater recharge, precipitation, potential evapotranspiration, and snow water equivalent. Impact Indicators have been co-designed with stakeholders in Norway (hydro-power), UK (water supply), and Spain (river basin authority) to provide an improved information for decision making. The Indicators encompass diverse information such as the occurrence of high and low streamflow percentiles (floods, and hydrological drought) and lower percentiles of top soil moisture (agricultural drought) among others. Preliminary results evaluated at study sites in Norway, Spain, and UK indicate that extreme events such as the 2003 European drought can be forecasted consistently by all models at short lead times of one to two months. At six month lead time, the 208 model realizations show little skill to forecast extreme events. The predictability of extreme events is not uniformly distributed across Europe. For example, Northern Europe exhibits higher predictability due to the persistence induced by cold processes (e.g., snow). In general, the major source of poor forecasting skill is the little skill in precipitation forecast. References http://climate.copernicus.eu/edge-end-end-demonstrator-improved-decision-making-water-sector-europe Bohn, T. J. , B., Livneh J. W. Oyler, S. W. Running, B. Nijssen, D. P. Lettenmaier, 2013: Global evaluation of MTCLIM and related algorithms for forcing of ecological and hydrological models. Agricultural and Forest Meteorology, 176 , pp. 38-49. Samaniego, L., R. Kumar, and S. Attinger (2010), Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resource Research, 46, W05523, doi:10.1029/2008WR007327 Thober, S., R. Kumar, J. Sheffield, J. Mai, D. Schaefer, and L. Samaniego, 2015: Seasonal soil moisture drought prediction over Europe using the North American Multi-Model Ensemble (NMME). J. Hydrometeor., 16, 2329-2344.

[A review on research of land surface water and heat fluxes].

PubMed

Sun, Rui; Liu, Changming

2003-03-01

Many field experiments were done, and soil-vegetation-atmosphere transfer(SVAT) models were stablished to estimate land surface heat fluxes. In this paper, the processes of experimental research on land surface water and heat fluxes are reviewed, and three kinds of SVAT model(single layer model, two layer model and multi-layer model) are analyzed. Remote sensing data are widely used to estimate land surface heat fluxes. Based on remote sensing and energy balance equation, different models such as simplified model, single layer model, extra resistance model, crop water stress index model and two source resistance model are developed to estimate land surface heat fluxes and evapotranspiration. These models are also analyzed in this paper.

Portable document format file showing the surface models of cadaver whole body.

PubMed

Shin, Dong Sun; Chung, Min Suk; Park, Jin Seo; Park, Hyung Seon; Lee, Sangho; Moon, Young Lae; Jang, Hae Gwon

2012-08-01

In the Visible Korean project, 642 three-dimensional (3D) surface models have been built from the sectioned images of a male cadaver. It was recently discovered that popular PDF file enables users to approach the numerous surface models conveniently on Adobe Reader. Purpose of this study was to present a PDF file including systematized surface models of human body as the beneficial contents. To achieve the purpose, fitting software packages were employed in accordance with the procedures. Two-dimensional (2D) surface models including the original sectioned images were embedded into the 3D surface models. The surface models were categorized into systems and then groups. The adjusted surface models were inserted to a PDF file, where relevant multimedia data were added. The finalized PDF file containing comprehensive data of a whole body could be explored in varying manners. The PDF file, downloadable freely from the homepage (http://anatomy.co.kr), is expected to be used as a satisfactory self-learning tool of anatomy. Raw data of the surface models can be extracted from the PDF file and employed for various simulations for clinical practice. The technique to organize the surface models will be applied to manufacture of other PDF files containing various multimedia contents.

FacetModeller: Software for manual creation, manipulation and analysis of 3D surface-based models

NASA Astrophysics Data System (ADS)

Lelièvre, Peter G.; Carter-McAuslan, Angela E.; Dunham, Michael W.; Jones, Drew J.; Nalepa, Mariella; Squires, Chelsea L.; Tycholiz, Cassandra J.; Vallée, Marc A.; Farquharson, Colin G.

2018-01-01

The creation of 3D models is commonplace in many disciplines. Models are often built from a collection of tessellated surfaces. To apply numerical methods to such models it is often necessary to generate a mesh of space-filling elements that conforms to the model surfaces. While there are meshing algorithms that can do so, they place restrictive requirements on the surface-based models that are rarely met by existing 3D model building software. Hence, we have developed a Java application named FacetModeller, designed for efficient manual creation, modification and analysis of 3D surface-based models destined for use in numerical modelling.

Verification and transfer of thermal pollution model. Volume 4: User's manual for three-dimensional rigid-lid model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Nwadike, E. V.; Sinha, S. E.

1982-01-01

The theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model are described. Model verification at two sites, a separate user's manual for each model are included. The 3-D model has two forms: free surface and rigid lid. The former allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth, estuaries and coastal regions. The latter is suited for small surface wave heights compared to depth because surface elevation was removed as a parameter. These models allow computation of time dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions. The free surface model also provides surface height variations with time.

Coupling surface water (Delft3D) to groundwater (MODFLOW) in the Bay-Delta community model: the effect of major abstractions in the Delta

NASA Astrophysics Data System (ADS)

Hendriks, D.; Ball, S. M.; Van der Wegen, M.; Verkaik, J.; van Dam, A.

2016-12-01

We present a coupled groundwater-surface water model for the San Francisco Bay and Sacramento Valley that consists of a combination of a spatially-distributed groundwater model (Modflow) based on the USGS Central Valley model(1) and the Flexible Mesh (FM) surface water model of the Bay Area(2). With this coupled groundwater-surface water model, we assessed effects of climate, surface water abstractions and groundwater pumping on surface water and groundwater levels, groundwater-surface water interaction and infiltration/seepage fluxes. Results show that the effect of climate (high flow and low flow) on surface water and groundwater is significant and most prominent in upstream areas. The surface water abstractions cause significant local surface water levels decrease (over 2 m), which may cause inflow of bay water during low flow periods, resulting in salinization of surface water in more upstream areas. Groundwater level drawdown due to surface water withdrawal is moderate and limited to the area of the withdrawals. The groundwater pumping causes large groundwater level drawdowns (up to 0.8 m) and significant changes in seepage/infiltration fluxes in the model. However, the effect on groundwater-surface water exchange is relatively small. The presented model instrument gives a sound first impression of the effects of climate and water abstraction on both surface water and groundwater. The combination of Modflow and Flexible Mesh has potential for modelling of groundwater-surface water exchange in deltaic areas, also in other parts of the world. However, various improvements need to be made in order to make the simulation results useful in practice. In addition, a water quality aspect could be added to assess salinization processes as well as groundwater-surface water aspects of water and soil pollution. (1) http://ca.water.usgs.gov/projects/central-valley/central-valley-hydrologic-model.html (2) www.d3d-baydelta.org

Space environment and lunar surface processes

NASA Technical Reports Server (NTRS)

Comstock, G. M.

1979-01-01

The development of a general rock/soil model capable of simulating in a self consistent manner the mechanical and exposure history of an assemblage of solid and loose material from submicron to planetary size scales, applicable to lunar and other space exposed planetary surfaces is discussed. The model was incorporated into a computer code called MESS.2 (model for the evolution of space exposed surfaces). MESS.2, which represents a considerable increase in sophistication and scope over previous soil and rock surface models, is described. The capabilities of previous models for near surface soil and rock surfaces are compared with the rock/soil model, MESS.2.

Measurement of deformations of models in a wind tunnel

NASA Astrophysics Data System (ADS)

Charpin, F.; Armand, C.; Selvaggini, R.

Techniques used at the ONERA Modane Center to monitor geometric variations in scale-models in wind tunnel trials are described. The methods include: photography of reflections from mirrors embedded in the model surface; laser-based torsiometry with polarized mirrors embedded in the model surface; predictions of the deformations using numerical codes for the model surface mechanical characteristics and the measured surface stresses; and, use of an optical detector to monitor the position of luminous fiber optic sources emitting from the model surfaces. The data enhance the confidence that the wind tunnel aerodynamic data will correspond with the in-flight performance of full scale flight surfaces.

Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

Treesearch

Patricia L. Andrews

2012-01-01

Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

Characterization, modeling and simulation of fused deposition modeling fabricated part surfaces

NASA Astrophysics Data System (ADS)

Taufik, Mohammad; Jain, Prashant K.

2017-12-01

Surface roughness is generally used for characterization, modeling and simulation of fused deposition modeling (FDM) fabricated part surfaces. But the average surface roughness is not able to provide the insight of surface characteristics with sharp peaks and deep valleys. It deals in the average sense for all types of surfaces, including FDM fabricated surfaces with distinct surface profile features. The present research work shows that kurtosis and skewness can be used for characterization, modeling and simulation of FDM surfaces because these roughness parameters have the ability to characterize a surface with sharp peaks and deep valleys. It can be critical in certain application areas in tribology and biomedicine, where the surface profile plays an important role. Thus, in this study along with surface roughness, skewness and kurtosis are considered to show a novel strategy to provide new transferable knowledge about FDM fabricated part surfaces. The results suggest that the surface roughness, skewness and kurtosis are significantly different at 0° and in the range (0°, 30°], [30°, 90°] of build orientation.

Fibronectin module FN(III)9 adsorption at contrasting solid model surfaces studied by atomistic molecular dynamics.

PubMed

Kubiak-Ossowska, Karina; Mulheran, Paul A; Nowak, Wieslaw

2014-08-21

The mechanism of human fibronectin adhesion synergy region (known as integrin binding region) in repeat 9 (FN(III)9) domain adsorption at pH 7 onto various and contrasting model surfaces has been studied using atomistic molecular dynamics simulations. We use an ionic model to mimic mica surface charge density but without a long-range electric field above the surface, a silica model with a long-range electric field similar to that found experimentally, and an Au {111} model with no partial charges or electric field. A detailed description of the adsorption processes and the contrasts between the various model surfaces is provided. In the case of our model silica surface with a long-range electrostatic field, the adsorption is rapid and primarily driven by electrostatics. Because it is negatively charged (-1e), FN(III)9 readily adsorbs to a positively charged surface. However, due to its partial charge distribution, FN(III)9 can also adsorb to the negatively charged mica model because of the absence of a long-range repulsive electric field. The protein dipole moment dictates its contrasting orientation at these surfaces, and the anchoring residues have opposite charges to the surface. Adsorption on the model Au {111} surface is possible, but less specific, and various protein regions might be involved in the interactions with the surface. Despite strongly influencing the protein mobility, adsorption at these model surfaces does not require wholesale FN(III)9 conformational changes, which suggests that the biological activity of the adsorbed protein might be preserved.

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

NASA Technical Reports Server (NTRS)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

Modelling hazardous surface hoar layers in the mountain snowpack over space and time

NASA Astrophysics Data System (ADS)

Horton, Simon Earl

Surface hoar layers are a common failure layer in hazardous snow slab avalanches. Surface hoar crystals (frost) initially form on the surface of the snow, and once buried can remain a persistent weak layer for weeks or months. Avalanche forecasters have difficulty tracking the spatial distribution and mechanical properties of these layers in mountainous terrain. This thesis presents numerical models and remote sensing methods to track the distribution and properties of surface hoar layers over space and time. The formation of surface hoar was modelled with meteorological data by calculating the downward flux of water vapour from the atmospheric boundary layer. The timing of surface hoar formation and the modelled crystal size was verified at snow study sites throughout western Canada. The major surface hoar layers over several winters were predicted with fair success. Surface hoar formation was modelled over various spatial scales using meteorological data from weather forecast models. The largest surface hoar crystals formed in regions and elevation bands with clear skies, warm and humid air, cold snow surfaces, and light winds. Field surveys measured similar regional-scale patterns in surface hoar distribution. Surface hoar formation patterns on different slope aspects were observed, but were not modelled reliably. Mechanical field tests on buried surface hoar layers found layers increased in shear strength over time, but had persistent high propensity for fracture propagation. Layers with large crystals and layers overlying hard melt-freeze crusts showed greater signs of instability. Buried surface hoar layers were simulated with the snow cover model SNOWPACK and verified with avalanche observations, finding most hazardous surface hoar layers were identified with a structural stability index. Finally, the optical properties of surface hoar crystals were measured in the field with spectral instruments. Large plate-shaped crystals were less reflective at shortwave infrared wavelengths than other common surface snow grains. The methods presented in this thesis were developed into operational products that model hazardous surface hoar layers in western Canada. Further research and refinements could improve avalanche forecasts in regions prone to hazardous surface hoar layers.

Further Investigations of Gravity Modeling on Surface-Interacting Vehicle Simulations

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2009-01-01

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of the gravitation and world model. A surface-interacting simulation cannot treat the gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a subsonic civil transport in level flight under various starting conditions.

Gravity Modeling Effects on Surface-Interacting Vehicles in Supersonic Flight

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2010-01-01

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations per-form ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of these two models. A surface-interacting simulation cannot treat gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a supersonic aircraft in level flight under various start-ing conditions.

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

A new class of actuator surface models for wind turbines

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Sotiropoulos, Fotis

2018-05-01

Actuator line model has been widely employed in wind turbine simulations. However, the standard actuator line model does not include a model for the turbine nacelle which can significantly impact turbine wake characteristics as shown in the literature. Another disadvantage of the standard actuator line model is that more geometrical features of turbine blades cannot be resolved on a finer mesh. To alleviate these disadvantages of the standard model, we develop a new class of actuator surface models for turbine blades and nacelle to take into account more geometrical details of turbine blades and include the effect of turbine nacelle. In the actuator surface model for blade, the aerodynamic forces calculated using the blade element method are distributed from the surface formed by the foil chords at different radial locations. In the actuator surface model for nacelle, the forces are distributed from the actual nacelle surface with the normal force component computed in the same way as in the direct forcing immersed boundary method and the tangential force component computed using a friction coefficient and a reference velocity of the incoming flow. The actuator surface model for nacelle is evaluated by simulating the flow over periodically placed nacelles. Both the actuator surface simulation and the wall-resolved large-eddy simulation are carried out. The comparison shows that the actuator surface model is able to give acceptable results especially at far wake locations on a very coarse mesh. It is noted that although this model is employed for the turbine nacelle in this work, it is also applicable to other bluff bodies. The capability of the actuator surface model in predicting turbine wakes is assessed by simulating the flow over the MEXICO (Model experiments in Controlled Conditions) turbine and a hydrokinetic turbine.

Velopharyngeal mucosal surface topography in healthy subjects and subjects with obstructive sleep apnea.

PubMed

Lambeth, Christopher; Amatoury, Jason; Wang, Ziyu; Foster, Sheryl; Amis, Terence; Kairaitis, Kristina

2017-03-01

Macroscopic pharyngeal anatomical abnormalities are thought to contribute to the pathogenesis of upper airway (UA) obstruction in obstructive sleep apnea (OSA). Microscopic changes in the UA mucosal lining of OSA subjects are reported; however, the impact of these changes on UA mucosal surface topography is unknown. This study aimed to 1 ) develop methodology to measure UA mucosal surface topography, and 2 ) compare findings from healthy and OSA subjects. Ten healthy and eleven OSA subjects were studied. Awake, gated (end expiration), head and neck position controlled magnetic resonance images (MRIs) of the velopharynx (VP) were obtained. VP mucosal surfaces were segmented from axial images, and three-dimensional VP mucosal surface models were constructed. Curvature analysis of the models was used to study the VP mucosal surface topography. Principal, mean, and Gaussian curvatures were used to define surface shape composition and surface roughness of the VP mucosal surface models. Significant differences were found in the surface shape composition, with more saddle/spherical and less flat/cylindrical shapes in OSA than healthy VP mucosal surface models ( P < 0.01). OSA VP mucosal surface models were also found to have more mucosal surface roughness ( P < 0.0001) than healthy VP mucosal surface models. Our novel methodology was utilized to model the VP mucosal surface of OSA and healthy subjects. OSA subjects were found to have different VP mucosal surface topography, composed of increased irregular shapes and increased roughness. We speculate increased irregularity in VP mucosal surface may increase pharyngeal collapsibility as a consequence of friction-related pressure loss. NEW & NOTEWORTHY A new methodology was used to model the upper airway mucosal surface topography from magnetic resonance images of patients with obstructive sleep apnea and healthy adults. Curvature analysis was used to analyze the topography of the models, and a new metric was derived to describe the mucosal surface roughness. Increased roughness was found in the obstructive sleep apnea vs. healthy group, but further research is required to determine the functional effects of the measured difference on upper airway airflow mechanics. Copyright © 2017 the American Physiological Society.

Climatic Models Ensemble-based Mid-21st Century Runoff Projections: A Bayesian Framework

NASA Astrophysics Data System (ADS)

Achieng, K. O.; Zhu, J.

2017-12-01

There are a number of North American Regional Climate Change Assessment Program (NARCCAP) climatic models that have been used to project surface runoff in the mid-21st century. Statistical model selection techniques are often used to select the model that best fits data. However, model selection techniques often lead to different conclusions. In this study, ten models are averaged in Bayesian paradigm to project runoff. Bayesian Model Averaging (BMA) is used to project and identify effect of model uncertainty on future runoff projections. Baseflow separation - a two-digital filter which is also called Eckhardt filter - is used to separate USGS streamflow (total runoff) into two components: baseflow and surface runoff. We use this surface runoff as the a priori runoff when conducting BMA of runoff simulated from the ten RCM models. The primary objective of this study is to evaluate how well RCM multi-model ensembles simulate surface runoff, in a Bayesian framework. Specifically, we investigate and discuss the following questions: How well do ten RCM models ensemble jointly simulate surface runoff by averaging over all the models using BMA, given a priori surface runoff? What are the effects of model uncertainty on surface runoff simulation?

Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

NASA Astrophysics Data System (ADS)

Sheng, Yongwei

2000-12-01

Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the canopy surface of a dense redwood stand using tri-ocular high-resolution images scanned from 1:2,400 aerial photographs. The results demonstrate the approach's ability to reconstruct complicated stands. The model-based approach proposed in this thesis is potentially applicable to other surfaces recovering problems with a priori knowledge about objects.

A solution to the surface intersection problem. [Boolean functions in geometric modeling

NASA Technical Reports Server (NTRS)

Timer, H. G.

1977-01-01

An application-independent geometric model within a data base framework should support the use of Boolean operators which allow the user to construct a complex model by appropriately combining a series of simple models. The use of these operators leads to the concept of implicitly and explicitly defined surfaces. With an explicitly defined model, the surface area may be computed by simply summing the surface areas of the bounding surfaces. For an implicitly defined model, the surface area computation must deal with active and inactive regions. Because the surface intersection problem involves four unknowns and its solution is a space curve, the parametric coordinates of each surface must be determined as a function of the arc length. Various subproblems involved in the general intersection problem are discussed, and the mathematical basis for their solution is presented along with a program written in FORTRAN IV for implementation on the IBM 370 TSO system.

A coarse grain model for protein-surface interactions

NASA Astrophysics Data System (ADS)

Wei, Shuai; Knotts, Thomas A.

2013-09-01

The interaction of proteins with surfaces is important in numerous applications in many fields—such as biotechnology, proteomics, sensors, and medicine—but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.

A diffuse radar scattering model from Martian surface rocks

NASA Technical Reports Server (NTRS)

Calvin, W. M.; Jakosky, B. M.; Christensen, P. R.

1987-01-01

Remote sensing of Mars has been done with a variety of instrumentation at various wavelengths. Many of these data sets can be reconciled with a surface model of bonded fines (or duricrust) which varies widely across the surface and a surface rock distribution which varies less so. A surface rock distribution map from -60 to +60 deg latitude has been generated by Christensen. Our objective is to model the diffuse component of radar reflection based on this surface distribution of rocks. The diffuse, rather than specular, scattering is modeled because the diffuse component arises due to scattering from rocks with sizes on the order of the wavelength of the radar beam. Scattering for radio waves of 12.5 cm is then indicative of the meter scale and smaller structure of the surface. The specular term is indicative of large scale surface undulations and should not be causally related to other surface physical properties. A simplified model of diffuse scattering is described along with two rock distribution models. The results of applying the models to a planet of uniform fractional rock coverage with values ranging from 5 to 20% are discussed.

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

2014-01-01

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

RIPPLE - A new model for incompressible flows with free surfaces

NASA Technical Reports Server (NTRS)

Kothe, D. B.; Mjolsness, R. C.

1991-01-01

A new free surface flow model, RIPPLE, is summarized. RIPPLE obtains finite difference solutions for incompressible flow problems having strong surface tension forces at free surfaces of arbitrarily complex topology. The key innovation is the continuum surface force model which represents surface tension as a (strongly) localized volume force. Other features include a higher-order momentum advection model, a volume-of-fluid free surface treatment, and an efficient two-step projection solution method. RIPPLE's unique capabilities are illustrated with two example problems: low-gravity jet-induced tank flow, and the collision and coalescence of two cylindrical rods.

Joint surface modeling with thin-plate splines.

PubMed

Boyd, S K; Ronsky, J L; Lichti, D D; Salkauskas, K; Chapman, M A; Salkauskas, D

1999-10-01

Mathematical joint surface models based on experimentally determined data points can be used to investigate joint characteristics such as curvature, congruency, cartilage thickness, joint contact areas, as well as to provide geometric information well suited for finite element analysis. Commonly, surface modeling methods are based on B-splines, which involve tensor products. These methods have had success; however, they are limited due to the complex organizational aspect of working with surface patches, and modeling unordered, scattered experimental data points. An alternative method for mathematical joint surface modeling is presented based on the thin-plate spline (TPS). It has the advantage that it does not involve surface patches, and can model scattered data points without experimental data preparation. An analytical surface was developed and modeled with the TPS to quantify its interpolating and smoothing characteristics. Some limitations of the TPS include discontinuity of curvature at exactly the experimental surface data points, and numerical problems dealing with data sets in excess of 2000 points. However, suggestions for overcoming these limitations are presented. Testing the TPS with real experimental data, the patellofemoral joint of a cat was measured with multistation digital photogrammetry and modeled using the TPS to determine cartilage thicknesses and surface curvature. The cartilage thickness distribution ranged between 100 to 550 microns on the patella, and 100 to 300 microns on the femur. It was found that the TPS was an effective tool for modeling joint surfaces because no preparation of the experimental data points was necessary, and the resulting unique function representing the entire surface does not involve surface patches. A detailed algorithm is presented for implementation of the TPS.

Verification and transfer of thermal pollution model. Volume 3: Verification of 3-dimensional rigid-lid model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Nwadike, E. V.; Sinha, S. K.

1982-01-01

The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter. These models allow computation of time-dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions. The free-surface model also provides surface height variations with time.

Light radiation pressure upon an optically orthotropic surface

NASA Astrophysics Data System (ADS)

Nerovny, Nikolay A.; Lapina, Irina E.; Grigorjev, Anton S.

2017-11-01

In this paper, we discuss the problem of determination of light radiation pressure force upon an anisotropic surface. The optical parameters of such a surface are considered to have major and minor axes, so the model is called an orthotropic model. We derive the equations for force components from emission, absorption, and reflection, utilizing a modified Maxwell's specular-diffuse model. The proposed model can be used to model a flat solar sail with wrinkles. By performing Bayesian analysis for example of a wrinkled surface, we show that there are cases in which an orthotropic model of the optical parameters of a surface may be more accurate than an isotropic model.

Simulations of surface winds at the Viking Lander sites using a one-level model

NASA Technical Reports Server (NTRS)

Bridger, Alison F. C.; Haberle, Robert M.

1992-01-01

The one-level model developed by Mass and Dempsey for use in predicting surface flows in regions of complex terrain was adapted to simulate surface flows at the Viking lander sites on Mars. In the one-level model, prediction equations for surface winds and temperatures are formulated and solved. Surface temperatures change with time in response to diabatic heating, horizontal advection, adiabatic heating and cooling effects, and horizontal diffusion. Surface winds can change in response to horizontal advection, pressure gradient forces, Coriolis forces, surface drag, and horizontal diffusion. Surface pressures are determined by integration of the hydrostatic equation from the surface to some reference level. The model has successfully simulated surface flows under a variety of conditions in complex-terrain regions on Earth.

A NEW LAND-SURFACE MODEL IN MM5

EPA Science Inventory

There has recently been a general realization that more sophisticated modeling of land-surface processes can be important for mesoscale meteorology models. Land-surface models (LSMs) have long been important components in global-scale climate models because of their more compl...

Modeling surface-water flow and sediment mobility with the Multi-Dimensional Surface-Water Modeling System (MD_SWMS)

USGS Publications Warehouse

McDonald, Richard; Nelson, Jonathan; Kinzel, Paul; Conaway, Jeffrey S.

2006-01-01

The Multi-Dimensional Surface-Water Modeling System (MD_SWMS) is a Graphical User Interface for surface-water flow and sediment-transport models. The capabilities of MD_SWMS for developing models include: importing raw topography and other ancillary data; building the numerical grid and defining initial and boundary conditions; running simulations; visualizing results; and comparing results with measured data.

Empirical Measurement and Model Validation of Infrared Spectra of Contaminated Surfaces

NASA Astrophysics Data System (ADS)

Archer, Sean

The goal of this thesis was to validate predicted infrared spectra of liquid contaminated surfaces from a micro-scale bi-directional reflectance distribution function (BRDF) model through the use of empirical measurement. Liquid contaminated surfaces generally require more sophisticated radiometric modeling to numerically describe surface properties. The Digital Image and Remote Sensing Image Generation (DIRSIG) model utilizes radiative transfer modeling to generate synthetic imagery for a variety of applications. Aside from DIRSIG, a micro-scale model known as microDIRSIG has been developed as a rigorous ray tracing physics-based model that could predict the BRDF of geometric surfaces that are defined as micron to millimeter resolution facets. The model offers an extension from the conventional BRDF models by allowing contaminants to be added as geometric objects to a micro-facet surface. This model was validated through the use of Fourier transform infrared spectrometer measurements. A total of 18 different substrate and contaminant combinations were measured and compared against modeled outputs. The substrates used in this experiment were wood and aluminum that contained three different paint finishes. The paint finishes included no paint, Krylon ultra-flat black, and Krylon glossy black. A silicon based oil (SF96) was measured out and applied to each surface to create three different contamination cases for each surface. Radiance in the longwave infrared region of the electromagnetic spectrum was measured by a Design and Prototypes (D&P) Fourier transform infrared spectrometer and a Physical Sciences Inc. Adaptive Infrared Imaging Spectroradiometer (AIRIS). The model outputs were compared against the measurements quantitatively in both the emissivity and radiance domains. A temperature emissivity separation (TES) algorithm had to be applied to the measured radiance spectra for comparison with the microDIRSIG predicted emissivity spectra. The model predicted emissivity spectra was also forward modeled through a DIRSIG simulation for comparisons to the radiance measurements. The results showed a promising agreement for homogeneous surfaces with liquid contamination that could be well characterized geometrically. Limitations arose in substrates that were modeled as homogeneous surfaces, but had spatially varying artifacts due to uncertainties with contaminant and surface interactions. There is high desire for accurate physics based modeling of liquid contaminated surfaces and this validation framework may be extended to include a wider array of samples for more realistic natural surfaces that are often found in real world scenarios.

Probabilistic storm surge inundation maps for Metro Manila based on Philippine public storm warning signals

NASA Astrophysics Data System (ADS)

Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

2015-03-01

A storm surge is the sudden rise of sea water over the astronomical tides, generated by an approaching storm. This event poses a major threat to the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013. This hydro-meteorological hazard is one of the main reasons for the high number of casualties due to the typhoon, with 6300 deaths. It became evident that the need to develop a storm surge inundation map is of utmost importance. To develop these maps, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. The Japan Meteorological Agency storm surge model was used to simulate storm surge heights. The frequency distribution of the maximum storm surge heights was calculated using simulation results of tropical cyclones under a specific public storm warning signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of inundation for a specific PSWS using the probability of exceedance derived from the frequency distribution. Buildings and other structures were assigned a probability of exceedance depending on their occupancy category, i.e., 1% probability of exceedance for critical facilities, 10% probability of exceedance for special occupancy structures, and 25% for standard occupancy and miscellaneous structures. The maps produced show the storm-surge-vulnerable areas in Metro Manila, illustrated by the flood depth of up to 4 m and extent of up to 6.5 km from the coastline. This information can help local government units in developing early warning systems, disaster preparedness and mitigation plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. These maps can also determine the best areas to build critical structures, or at least determine the level of protection of these structures should they be built in hazard areas. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate countermeasures for a given PSWS.

Study of Near-Surface Models in Large-Eddy Simulations of a Neutrally Stratified Atmospheric Boundary Layer

NASA Technical Reports Server (NTRS)

Senocak, I.; Ackerman, A. S.; Kirkpatrick, M. P.; Stevens, D. E.; Mansour, N. N.

2004-01-01

Large-eddy simulation (LES) is a widely used technique in armospheric modeling research. In LES, large, unsteady, three dimensional structures are resolved and small structures that are not resolved on the computational grid are modeled. A filtering operation is applied to distinguish between resolved and unresolved scales. We present two near-surface models that have found use in atmospheric modeling. We also suggest a simpler eddy viscosity model that adopts Prandtl's mixing length model (Prandtl 1925) in the vicinity of the surface and blends with the dynamic Smagotinsky model (Germano et al, 1991) away from the surface. We evaluate the performance of these surface models by simulating a neutraly stratified atmospheric boundary layer.

Modeling uranium(VI) adsorption onto montmorillonite under varying carbonate concentrations: A surface complexation model accounting for the spillover effect on surface potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tournassat, C.; Tinnacher, R. M.; Grangeon, S.

The prediction of U(VI) adsorption onto montmorillonite clay is confounded by the complexities of: (1) the montmorillonite structure in terms of adsorption sites on basal and edge surfaces, and the complex interactions between the electrical double layers at these surfaces, and (2) U(VI) solution speciation, which can include cationic, anionic and neutral species. Previous U(VI)-montmorillonite adsorption and modeling studies have typically expanded classical surface complexation modeling approaches, initially developed for simple oxides, to include both cation exchange and surface complexation reactions. However, previous models have not taken into account the unique characteristics of electrostatic surface potentials that occur at montmorillonitemore » edge sites, where the electrostatic surface potential of basal plane cation exchange sites influences the surface potential of neighboring edge sites (‘spillover’ effect).« less

Modeling uranium(VI) adsorption onto montmorillonite under varying carbonate concentrations: A surface complexation model accounting for the spillover effect on surface potential

DOE PAGES

Tournassat, C.; Tinnacher, R. M.; Grangeon, S.; ...

2017-10-06

The prediction of U(VI) adsorption onto montmorillonite clay is confounded by the complexities of: (1) the montmorillonite structure in terms of adsorption sites on basal and edge surfaces, and the complex interactions between the electrical double layers at these surfaces, and (2) U(VI) solution speciation, which can include cationic, anionic and neutral species. Previous U(VI)-montmorillonite adsorption and modeling studies have typically expanded classical surface complexation modeling approaches, initially developed for simple oxides, to include both cation exchange and surface complexation reactions. However, previous models have not taken into account the unique characteristics of electrostatic surface potentials that occur at montmorillonitemore » edge sites, where the electrostatic surface potential of basal plane cation exchange sites influences the surface potential of neighboring edge sites (‘spillover’ effect).« less

Anthropogenic Warming Impacts on Today's Sierra Nevada Snowpack and Flood Severity

NASA Astrophysics Data System (ADS)

Huang, X.; Hall, A. D.; Berg, N.

2017-12-01

Focusing on this recent extreme wet year over California, this study investigates the warming impacts on the snowpack and the flood severity over the Sierra Nevada (SN), where the majority of the precipitation occurs during the winter season and early spring. One of our goals is to quantify anthropogenic warming impacts on the snow water equivalent (SWE) including recent historical warming and prescribed future projected warming scenarios; This work also explores to what extent flooding risk has increased under those warming cases. With a good representation of the historical precipitation and snowpack over the Sierra Nevada from the historical reference run at 9km (using WRF), the results from the offline Noah-MP simulations with perturbed near-surface temperatures reveal magnificent impacts of warming to the loss of the average snowpack. The reduction of the SWE under warming mainly results from the decreased rain-to-snow conversion with a weaker effect from increased snowmelt. Compared to the natural case, the past industrial warming decreased the maximum SWE by about one-fifth averaged over the study area. Future continuing warming can result in around one-third reduction of current maximum SWE under RCP4.5 emissions scenario, and the loss can reach to two-thirds under RCP8.5 as a "business-as-usual" condition. The impact of past warming is particularly outstanding over the North SN region where precipitation dominates and over the middle elevation regions where the snow mainly distributes. In the future, the warming impact on SWE progresses to higher regions, and so to the south and east. Under the business-as-usual scenario, the projected mid-elevation snowpack almost disappears by April 1st with even high-elevation snow reduced by about half. Along with the loss of the snowpack, as the temperature warms, floods can also intensify with increased early season runoff especially under heavy-rainy days caused by the weakened rain-to-snow processes and strengthened snow-melt mainly over the mid-elevation region. Under continuing warming and predicted intensified precipitation extremes in the coming century, the severity of floods can become much more disastrous and potentially shift from the north (where the Oroville Dam spillway emergency occurred this February) to the central and south SN regions.

Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

NASA Astrophysics Data System (ADS)

Huang, Shih-Yu; Deng, Yi; Wang, Jingfeng

2017-09-01

The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration-Clouds and the Earth's Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

Comparison of Response Surface and Kriging Models for Multidisciplinary Design Optimization

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.; Korte, John J.; Mauery, Timothy M.; Mistree, Farrokh

1998-01-01

In this paper, we compare and contrast the use of second-order response surface models and kriging models for approximating non-random, deterministic computer analyses. After reviewing the response surface method for constructing polynomial approximations, kriging is presented as an alternative approximation method for the design and analysis of computer experiments. Both methods are applied to the multidisciplinary design of an aerospike nozzle which consists of a computational fluid dynamics model and a finite-element model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations, and four optimization problems m formulated and solved using both sets of approximation models. The second-order response surface models and kriging models-using a constant underlying global model and a Gaussian correlation function-yield comparable results.

Digital terrain modeling and industrial surface metrology: Converging realms

USGS Publications Warehouse

Pike, R.J.

2001-01-01

Digital terrain modeling has a micro-and nanoscale counterpart in surface metrology, the numerical characterization of industrial surfaces. Instrumentation in semiconductor manufacturing and other high-technology fields can now contour surface irregularities down to the atomic scale. Surface metrology has been revolutionized by its ability to manipulate square-grid height matrices that are analogous to the digital elevation models (DEMs) used in physical geography. Because the shaping of industrial surfaces is a spatial process, the same concepts of analytical cartography that represent ground-surface form in geography evolved independently in metrology: The surface topography of manufactured components, exemplified here by automobile-engine cylinders, is routinely modeled by variogram analysis, relief shading, and most other techniques of parameterization and visualization familiar to geography. This article introduces industrial surface-metrology, examines the field in the context of terrain modeling and geomorphology and notes their similarities and differences, and raises theoretical issues to be addressed in progressing toward a unified practice of surface morphometry.

Some aerodynamic considerations related to wind tunnel model surface definition

NASA Technical Reports Server (NTRS)

Gloss, B. B.

1980-01-01

The aerodynamic considerations related to model surface definition are examined with particular emphasis in areas of fabrication tolerances, model surface finish, and orifice induced pressure errors. The effect of model surface roughness texture on skin friction is also discussed. It is shown that at a given Reynolds number, any roughness will produce no skin friction penalty.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Cliff

2015-01-01

Empirical models for the shielding and refection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and rejection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Clifford A.

2016-01-01

Empirical models for the shielding and reflection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and reflection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Fast, Statistical Model of Surface Roughness for Ion-Solid Interaction Simulations and Efficient Code Coupling

NASA Astrophysics Data System (ADS)

Drobny, Jon; Curreli, Davide; Ruzic, David; Lasa, Ane; Green, David; Canik, John; Younkin, Tim; Blondel, Sophie; Wirth, Brian

2017-10-01

Surface roughness greatly impacts material erosion, and thus plays an important role in Plasma-Surface Interactions. Developing strategies for efficiently introducing rough surfaces into ion-solid interaction codes will be an important step towards whole-device modeling of plasma devices and future fusion reactors such as ITER. Fractal TRIDYN (F-TRIDYN) is an upgraded version of the Monte Carlo, BCA program TRIDYN developed for this purpose that includes an explicit fractal model of surface roughness and extended input and output options for file-based code coupling. Code coupling with both plasma and material codes has been achieved and allows for multi-scale, whole-device modeling of plasma experiments. These code coupling results will be presented. F-TRIDYN has been further upgraded with an alternative, statistical model of surface roughness. The statistical model is significantly faster than and compares favorably to the fractal model. Additionally, the statistical model compares well to alternative computational surface roughness models and experiments. Theoretical links between the fractal and statistical models are made, and further connections to experimental measurements of surface roughness are explored. This work was supported by the PSI-SciDAC Project funded by the U.S. Department of Energy through contract DOE-DE-SC0008658.

Simple model of surface roughness for binary collision sputtering simulations

NASA Astrophysics Data System (ADS)

Lindsey, Sloan J.; Hobler, Gerhard; Maciążek, Dawid; Postawa, Zbigniew

2017-02-01

It has been shown that surface roughness can strongly influence the sputtering yield - especially at glancing incidence angles where the inclusion of surface roughness leads to an increase in sputtering yields. In this work, we propose a simple one-parameter model (the "density gradient model") which imitates surface roughness effects. In the model, the target's atomic density is assumed to vary linearly between the actual material density and zero. The layer width is the sole model parameter. The model has been implemented in the binary collision simulator IMSIL and has been evaluated against various geometric surface models for 5 keV Ga ions impinging an amorphous Si target. To aid the construction of a realistic rough surface topography, we have performed MD simulations of sequential 5 keV Ga impacts on an initially crystalline Si target. We show that our new model effectively reproduces the sputtering yield, with only minor variations in the energy and angular distributions of sputtered particles. The success of the density gradient model is attributed to a reduction of the reflection coefficient - leading to increased sputtering yields, similar in effect to surface roughness.

Reverse engineering of aircraft wing data using a partial differential equation surface model

NASA Astrophysics Data System (ADS)

Huband, Jacalyn Mann

Reverse engineering is a multi-step process used in industry to determine a production representation of an existing physical object. This representation is in the form of mathematical equations that are compatible with computer-aided design and computer-aided manufacturing (CAD/CAM) equipment. The four basic steps to the reverse engineering process are data acquisition, data separation, surface or curve fitting, and CAD/CAM production. The surface fitting step determines the design representation of the object, and thus is critical to the success or failure of the reverse engineering process. Although surface fitting methods described in the literature are used to model a variety of surfaces, they are not suitable for reversing aircraft wings. In this dissertation, we develop and demonstrate a new strategy for reversing a mathematical representation of an aircraft wing. The basis of our strategy is to take an aircraft design model and determine if an inverse model can be derived. A candidate design model for this research is the partial differential equation (PDE) surface model, proposed by Bloor and Wilson and used in the Rapid Airplane Parameter Input Design (RAPID) tool at the NASA-LaRC Geolab. There are several basic mathematical problems involved in reversing the PDE surface model: (i) deriving a computational approximation of the surface function; (ii) determining a radial parametrization of the wing; (iii) choosing mathematical models or classes of functions for representation of the boundary functions; (iv) fitting the boundary data points by the chosen boundary functions; and (v) simultaneously solving for the axial parameterization and the derivative boundary functions. The study of the techniques to solve the above mathematical problems has culminated in a reverse PDE surface model and two reverse PDE surface algorithms. One reverse PDE surface algorithm recovers engineering design parameters for the RAPID tool from aircraft wing data and the other generates a PDE surface model with spline boundary functions from an arbitrary set of grid points. Our numerical tests show that the reverse PDE surface model and the reverse PDE surface algorithms can be used for the reverse engineering of aircraft wing data.

User's manual for master: Modeling of aerodynamic surfaces by 3-dimensional explicit representation. [input to three dimensional computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gibson, S. G.

1983-01-01

A system of computer programs was developed to model general three dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinates, to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface/surface intersection curves. Input and output data formats are described; detailed suggestions are given for user input. Instructions for execution are given, and examples are shown.

A soil-canopy scheme for use in a numerical model of the atmosphere: 1D stand-alone model

NASA Astrophysics Data System (ADS)

Kowalczyk, E. A.; Garratt, J. R.; Krummel, P. B.

We provide a detailed description of a soil-canopy scheme for use in the CSIRO general circulation models (GCMs) (CSIRO-4 and CSIRO-9), in the form of a one-dimensional stand-alone model. In addition, the paper documents the model's ability to simulate realistic surface fluxes by comparison with mesoscale model simulations (involving more sophisticated soil and boundary-layer treatments) and observations, and the diurnal range in surface quantities, including extreme maximum surface temperatures. The sensitivity of the model to values of the surface resistance is also quantified. The model represents phase 1 of a longer-term plan to improve the atmospheric boundary layer (ABL) and surface schemes in the CSIRO GCMs.

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET outputs.

Heating requirements and nonadiabatic surface effects for a model in the NTF cryogenic wind tunnel

NASA Technical Reports Server (NTRS)

Macha, J. M.; Landrum, D. B.; Pare, L. A., III; Johnson, C. B.

1988-01-01

A theoretical study has been made of the severity of nonadiabatic surface conditions arising from internal heat sources within a model in a cryogenic wind tunnel. Local surface heating is recognized as having an effect on the development of the boundary layer, which can introduce changes in the flow about the model and affect the wind tunnel data. The geometry was based on the NTF Pathfinder I wind tunnel model. A finite element heat transfer computer code was developed and used to compute the steady state temperature distribution within the body of the model, from which the surface temperature distribution was extracted. Particular three dimensional characteristics of the model were represented with various axisymmetric approximations of the geometry. This analysis identified regions on the surface of the model susceptible to surface heating and the magnitude of the respective surface temperatures. It was found that severe surface heating may occur in particular instances, but could be alleviated with adequate insulating material. The heat flux through the surface of the model was integrated to determine the net heat required to maintain the instrumentation cavity at the prescribed temperature. The influence of the nonadiabatic condition on boundary layer properties and on the validity of the wind tunnel simulation was also investigated.

Assessing the Increase in Specific Surface Area for Electrospun Fibrous Network due to Pore Induction.

PubMed

Katsogiannis, Konstantinos Alexandros G; Vladisavljević, Goran T; Georgiadou, Stella; Rahmani, Ramin

2016-10-26

The effect of pore induction on increasing electrospun fibrous network specific surface area was investigated in this study. Theoretical models based on the available surface area of the fibrous network and exclusion of the surface area lost due to fiber-to-fiber contacts were developed. The models for calculation of the excluded area are based on Hertzian, Derjaguin-Muller-Toporov (DMT), and Johnson-Kendall-Roberts (JKR) contact models. Overall, the theoretical models correlated the network specific surface area to the material properties including density, surface tension, Young's modulus, Poisson's ratio, as well as network physical properties, such as density and geometrical characteristics including fiber radius, fiber aspect ratio and network thickness. Pore induction proved to increase the network specific surface area up to 52%, compared to the maximum surface area that could be achieved by nonporous fiber network with the same physical properties and geometrical characteristics. The model based on Johnson-Kendall-Roberts contact model describes accurately the fiber-to-fiber contact area under the experimental conditions used for pore generation. The experimental results and the theoretical model based on Johnson-Kendall-Roberts contact model show that the increase in network surface area due to pore induction can reach to up to 58%.

Magnetic Flux Transport at the Solar Surface

NASA Astrophysics Data System (ADS)

Jiang, J.; Hathaway, D. H.; Cameron, R. H.; Solanki, S. K.; Gizon, L.; Upton, L.

2014-12-01

After emerging to the solar surface, the Sun's magnetic field displays a complex and intricate evolution. The evolution of the surface field is important for several reasons. One is that the surface field, and its dynamics, sets the boundary condition for the coronal and heliospheric magnetic fields. Another is that the surface evolution gives us insight into the dynamo process. In particular, it plays an essential role in the Babcock-Leighton model of the solar dynamo. Describing this evolution is the aim of the surface flux transport model. The model starts from the emergence of magnetic bipoles. Thereafter, the model is based on the induction equation and the fact that after emergence the magnetic field is observed to evolve as if it were purely radial. The induction equation then describes how the surface flows—differential rotation, meridional circulation, granular, supergranular flows, and active region inflows—determine the evolution of the field (now taken to be purely radial). In this paper, we review the modeling of the various processes that determine the evolution of the surface field. We restrict our attention to their role in the surface flux transport model. We also discuss the success of the model and some of the results that have been obtained using this model.

Predictive model for ice formation on superhydrophobic surfaces.

PubMed

Bahadur, Vaibhav; Mishchenko, Lidiya; Hatton, Benjamin; Taylor, J Ashley; Aizenberg, Joanna; Krupenkin, Tom

2011-12-06

The prevention and control of ice accumulation has important applications in aviation, building construction, and energy conversion devices. One area of active research concerns the use of superhydrophobic surfaces for preventing ice formation. The present work develops a physics-based modeling framework to predict ice formation on cooled superhydrophobic surfaces resulting from the impact of supercooled water droplets. This modeling approach analyzes the multiple phenomena influencing ice formation on superhydrophobic surfaces through the development of submodels describing droplet impact dynamics, heat transfer, and heterogeneous ice nucleation. These models are then integrated together to achieve a comprehensive understanding of ice formation upon impact of liquid droplets at freezing conditions. The accuracy of this model is validated by its successful prediction of the experimental findings that demonstrate that superhydrophobic surfaces can fully prevent the freezing of impacting water droplets down to surface temperatures of as low as -20 to -25 °C. The model can be used to study the influence of surface morphology, surface chemistry, and fluid and thermal properties on dynamic ice formation and identify parameters critical to achieving icephobic surfaces. The framework of the present work is the first detailed modeling tool developed for the design and analysis of surfaces for various ice prevention/reduction strategies. © 2011 American Chemical Society

Biochemical and biophysical characterization of cell-free synthesized Rift Valley fever virus nucleoprotein capsids enables in vitro screening to identify novel antivirals.

PubMed

Broce, Sean; Hensley, Lisa; Sato, Tomoharu; Lehrer-Graiwer, Joshua; Essrich, Christian; Edwards, Katie J; Pajda, Jacqueline; Davis, Christopher J; Bhadresh, Rami; Hurt, Clarence R; Freeman, Beverly; Lingappa, Vishwanath R; Kelleher, Colm A; Karpuj, Marcela V

2016-05-14

Viral capsid assembly involves the oligomerization of the capsid nucleoprotein (NP), which is an essential step in viral replication and may represent a potential antiviral target. An in vitro transcription-translation reaction using a wheat germ (WG) extract in combination with a sandwich ELISA assay has recently been used to identify small molecules with antiviral activity against the rabies virus. Here, we examined the application of this system to viruses with capsids with a different structure, such as the Rift Valley fever virus (RVFV), the etiological agent of a severe emerging infectious disease. The biochemical and immunological characterization of the in vitro-generated RVFV NP assembly products enabled the distinction between intermediately and highly ordered capsid structures. This distinction was used to establish a screening method for the identification of potential antiviral drugs for RVFV countermeasures. These results indicated that this unique analytical system, which combines nucleoprotein oligomerization with the specific immune recognition of a highly ordered capsid structure, can be extended to various viral families and used both to study the early stages of NP assembly and to assist in the identification of potential antiviral drugs in a cost-efficient manner. Reviewed by Jeffry Skolnick and Noah Isakov. For the full reviews please go to the Reviewers' comments section.

Anomalous scaling of stochastic processes and the Moses effect

NASA Astrophysics Data System (ADS)

Chen, Lijian; Bassler, Kevin E.; McCauley, Joseph L.; Gunaratne, Gemunu H.

2017-04-01

The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t1/2. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.

The impact of future climate on historic interiors.

PubMed

Lankester, Paul; Brimblecombe, Peter

2012-02-15

The socio-economic significance of climate change is widely recognised. However, its potential to affect our cultural heritage has not been discussed in detail (i.e. not explicit in IPCC 4) even though the cultural impacts of future outdoor climate have been the focus of some European Commission projects (e.g. NOAH'S ARK) and World Heritage Centre reports. Recently there have been a few projects that have examined the changing environmental threats to tangible heritage indoors (e.g. Preparing Historic Collections for Climate Change and Climate for Culture). Here we predict future indoor temperature and humidity, and damage arising from changes to climate in historic rooms in Southern England with little climate control, using simple building simulations coupled with high resolution (~5 km) climate predictions. The calculations suggest an increase in indoor temperature over the next century that is slightly less than that outdoors. Annual relative humidity shows little change, but the seasonal cycles suggest drier summers and slightly damper winters indoors. Damage from mould growth and pests is likely to increase in the future, while humidity driven dimensional change to materials (e.g. wood) should decrease somewhat. The results allow collection managers to prepare for the impact of long-term climate change, putting strategic measures in place to prevent increased damage, and thus preserve our heritage for future generations. Copyright © 2011 Elsevier B.V. All rights reserved.

Status and future of MUSE

NASA Astrophysics Data System (ADS)

Harfst, S.; Portegies Zwart, S.; McMillan, S.

2008-12-01

We present MUSE, a software framework for combining existing computational tools from different astrophysical domains into a single multi-physics, multi-scale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a ``Noah's Ark'' milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multi-scale and multi-physics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe two examples calculated using MUSE: the merger of two galaxies and an N-body simulation with live stellar evolution. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.li.

The Wandering Indian Plate and Its Changing Biogeography During the Late Cretaceous-Early Tertiary Period

NASA Astrophysics Data System (ADS)

Chatterjee, Sankar; Scotese, Christopher

Palaeobiogeographic analysis of Indian tetrapods during the Late Cretaceous-Early Tertiary time has recognized that both vicariance and geodispersal have played important roles in producing biogeographic congruence. The biogeographic patterns show oscillating cycles of geodispersal (Late Cretaceous), followed by congruent episodes of vicariance and geodispersal (Early Eocene), followed by another geodispersal event (Middle Eocene). New biogeographic synthesis suggests that the Late Cretaceous Indian tetrapod fauna is cosmopolitan with both Gondwanan and Laurasian elements. Throughout most of the Cretaceous, India was separated from the rest of Gondwana, but in the latest Cretaceous it reestablished contact with Africa through Kohistan-Dras (K-D) volcanic arc, and maintained biotic link with South America via Ninetyeast Ridge-Kerguelen-Antarctica corridor. These two geodispersal routes allowed exchanges of "pan-Gondwana" terrestrial tetrapods from Africa, South America, and Madagascar. During that time India also maintained biotic connections with Laurasia across the Neotethys via Kohistan-Dras Arc and Africa. During the Palaeocene, India, welded to the K-D Arc, rafted like a "Noah's Ark" as an island continent and underwent rapid cladogenesis because of allopatric speciation. Although the Palaeocene fossil record is blank, Early Eocene tetrapods contain both endemic and cosmopolitan elements, but Middle Eocene faunas have strong Asian character. India collided with Asia in Early and Middle Eocene time and established a new northeast corridor for faunal migration to facilitate the bidirectional "Great Asian Interchange" dispersals.

Anomalous scaling of stochastic processes and the Moses effect.

PubMed

Chen, Lijian; Bassler, Kevin E; McCauley, Joseph L; Gunaratne, Gemunu H

2017-04-01

The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t^{1/2}. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.

The Creation of Space Vector Models of Buildings From RPAS Photogrammetry Data

NASA Astrophysics Data System (ADS)

Trhan, Ondrej

2017-06-01

The results of Remote Piloted Aircraft System (RPAS) photogrammetry are digital surface models and orthophotos. The main problem of the digital surface models obtained is that buildings are not perpendicular and the shape of roofs is deformed. The task of this paper is to obtain a more accurate digital surface model using building reconstructions. The paper discusses the problem of obtaining and approximating building footprints, reconstructing the final spatial vector digital building model, and modifying the buildings on the digital surface model.